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Review

The Importance of Murine Models in Determining In Vivo Pharmacokinetics, Safety, and Efficacy in Antimalarial Drug Discovery

1
Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota PMB 1023, Nigeria
2
Department of Biological Sciences, College of Science and Technology, Covenant University, Ota PMB 1023, Nigeria
3
Biochemistry and Nutrition Division, Nigerian Institute of Medical Research, Yaba PMB 2013, Nigeria
4
Swiss Tropical and Public Health Institute, Kreuzstrasse 2, CH-4123 Allschwil, Switzerland
5
Department of Chemistry, College of Science and Technology, Covenant University, Ota PMB 1023, Nigeria
6
Department of Biochemistry and Sports Science, College of Natural Sciences, Makerere University, Kampala P.O. Box 7062, Uganda
7
Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
8
African Centre of Excellence in Bioinformatics & Data Intensive Science (ACE), Kampala P.O. Box 7062, Uganda
9
Infectious Diseases Institute, Makerere University, Kampala P.O. Box 22418, Uganda
*
Authors to whom correspondence should be addressed.
Pharmaceuticals 2025, 18(3), 424; https://doi.org/10.3390/ph18030424
Submission received: 21 January 2025 / Revised: 10 March 2025 / Accepted: 13 March 2025 / Published: 18 March 2025
(This article belongs to the Special Issue Antimalarial Drug Candidates)

Abstract

:
New chemical entities are constantly being investigated towards antimalarial drug discovery, and they require animal models for toxicity and efficacy testing. Murine models show physiological similarities to humans and are therefore indispensable in the search for novel antimalarial drugs. They provide a preclinical basis (following in vitro assessments of newly identified lead compounds) for further assessment in the drug development pipeline. Specific mouse strains, non-humanized and humanized, have successfully been infected with rodent Plasmodium species and the human Plasmodium species, respectively. Infected mice provide a platform for the assessment of treatment options being sought. In vivo pharmacokinetic evaluations are necessary when determining the fate of potential antimalarials in addition to the efficacy assessment of these chemical entities. This review describes the role of murine models in the drug development pipeline. It also explains some in vivo pharmacokinetic, safety, and efficacy parameters necessary for making appropriate choices of lead compounds in antimalarial drug discovery. Despite the advantages of murine models in antimalarial drug discovery, certain limitations are also highlighted.

Graphical Abstract

1. Introduction

The Global Technical Strategy for Malaria has maintained a responsibility to facilitate the global eradication of malaria through salient measures [1]. Major drivers of malaria elimination are the control efforts galvanized into achieving great strides in the global eradication pursuit [2]. Global malaria control efforts rely on a combination of modern diagnostic tools, preventive strategies, and effective treatment measures [2]. As a key factor of the treatment measure, the effectiveness of existing medications has seen a decline over the years as a result of drug resistance [3]. This has posed a notable challenge and has influenced unrelenting continuous efforts towards the discovery and development of new antimalarial drugs [4]. The discovery and development of new antimalarial entities focus on evading the drug resistance hurdle and embracing increased effectiveness with suitable dosage regimens [5]. Novel drug entities are also being discovered based on specific targets and newly identified mechanisms of action [5,6]. Potent novel entities are prioritized based on their fast antimalarial action and capacity to evade drug resistance hurdles as determined by their pharmacodynamic and pharmacokinetic profiles [7].
Due to the significant amount of time required to begin the antimalarial drug discovery process from natural sources, modern antimalarial drug discovery has employed computational and technological tools to develop computer-aided potential antimalarial compounds by virtual screening as an initiation into the drug discovery pipeline [7,8]. The discovery of new chemical entities through high-throughput screening of thousands of potentially active compounds is an early step into the drug discovery pipeline [7,8,9]. In silico-based predicted ligands are prioritized based on their predicted binding affinity to specific target proteins and the molecular dynamics associated with the ligand interactions [10]. Predicted pharmacokinetic and physicochemical properties aid in filtering through identified potential compounds that may be active early lead compounds [8]. Early leads then undergo optimization procedures, and the successful ones are further analyzed. Once optimized and passing all required in vivo tests as outlined by the Medicine for Malaria Ventures (MMV), the resulting compounds may proceed as antimalarial preclinical candidates (Figure 1) [5].
Computer-aided drug design and high-throughput screens are necessary to identify specific potent compounds (hits) from a library of potential compounds. Selected hits undergo rigorous in vitro assessments including pharmacodynamic and safety screens. Compounds showing the best activities following the in vitro assessments may become lead compounds that undergo in vivo screenings, such as antimalarial efficacy, pharmacokinetics, and toxicity assessments. Compounds showing the best activities move on to become preclinical candidates.
Animal models (in vivo) (Table 1) are part and parcel of the antimalarial drug discovery venture [5]. Hamsters (Mesocricetus auratus), mice (Mus musculus), rats (Rattus species), dogs (Canis lupus familiaris), and macaques (Macaca species) are commonly employed as animal models during the drug discovery process. Murine models are currently being explored in other areas of malaria research besides drug discovery, emphasizing their indispensable utility. Humanized mice are primarily used during efficacy studies in the drug discovery process [5,11,12]. The selection of an animal model for in vivo evaluations depends on the degree of similarity between the target protein in the rodent and the human parasite [13]. These animal models are necessary for predicting drug responses in humans [14]. In addition, murine (mice) models are considered more accessible and versatile, hence their preference over other animal species in early drug discovery [13,15].
Despite the advantages of the murine model, alternative preclinical models can be explored in the absence of mice. Macaques have been used in the evaluation of efficacy, pharmacokinetics, and toxicity of potential antimalarials in drug discovery [16,17]. They have been leveraged as an experimental model in malaria vaccine development [18,19]. Macaca species are primarily inoculated with Plasmodium knowlesi [20]. Hamsters were successfully inoculated with P. berghei malaria [21,22], and several studies have been conducted in the treatment of Leishmania species or Schistosoma species in hamsters using antimalarial drugs [23,24]. This suggests that hamsters may be an eligible experimental model for drug screening in antimalarial drug discovery. Dogs are commonly and primarily used to determine the pharmacokinetic and toxicity properties of lead compounds in the antimalarial drug discovery process [25,26]. Rattus species are commonly used to determine the efficacy, pharmacokinetic, and safety properties of lead compounds in antimalarial drug discovery [27,28].
Table 1. Experimental models used in antimalarial drug discovery.
Table 1. Experimental models used in antimalarial drug discovery.
Experimental ModelsStudy Type in Antimalarial Drug DiscoveryPlasmodium Species InoculatedReferences
Macaca speciesEfficacy,
Pharmacokinetics,
Toxicity
Plasmodium knowlesi[16,17,20]
Mesocricetus auratus-Plasmodium berghei[21,22]
Canis lupus familiarisPharmacokinetics,
Toxicity
-[25,26]
Rattus speciesEfficacy
Pharmacokinetics,
Toxicity
Plasmodium berghei[27,28]
The discovery of new antimalarials employing murine models for investigative purposes, including efficacy, vaccine development, and safety, dates back decades [29]. Human physiology and genetics are closely related to murine models, providing many opportunities to explore malaria research [30]. Humans and mice share 99% similar conserved regions of their genome [31]. Understanding murine responses in host–pathogen interactions during malaria infection or drug discovery provides insights into the possible parallel outcomes in humans, especially when murine strains are passaged with the susceptible rodent Plasmodium strains [30]. Genetic engineering is also used to manipulate rodents to produce transgenic strains. Humanized mice models are the outcomes of these manipulations; they are, therefore, beneficial to different experimental designs in malaria research [32]. Despite the similarities between human malarial infection and malaria infection in murine models, there are specific differences, such as P. berghei hepatocytic development occurring faster than P. falciparum hepatocytic development [33,34] and the presence of two thiamin biosynthesis enzymes that participate in decreasing the parasite’s proliferative capacity in P. falciparum, which is absent in P. berghei [35]; Kelch 13 (associated with artemisinin resistance) protein is constituted of 726 amino acids in P. falciparum but 738 are found in P. berghei among other differences [36]. These and other differences could hinder the absolute application of results obtained from mice malaria research in human malaria research.
Some of the advantages of murine models over other animal species used in antimalarial drug discovery include the following:
  • Mice genes can be manipulated [30].
  • Tissue sections are accessible for examination in case of histopathology [13,37].
  • This animal model is miniature-sized and can be handled easily [38].
  • Mouse models are affordable [38].
The rodent malaria Plasmodium species are Plasmodium berghei, Plasmodium chabaudi, Plasmodium vinckei, and Plasmodium yoelii. P. berghei ANKA strain infects murine models and is used as a model for P. falciparum infection in humans [39]. P. berghei ANKA and P. yoelii 17XL confer lethality during infection in mice and, therefore, serve as a model for severe malaria [40]. Meanwhile, 17XNL P. yoelii confers non-lethality and has been used as a model in malaria vaccine development [41]. P. chabaudi provides a great representation of the human malaria pathology and immunology. P. vinckei exists as both lethal and non-lethal strains [42]. Overall, the rodent malaria models are more straightforward to use during drug discovery than during vaccine development, as it is easier to protect mice from malaria infection than humans [43].

2. Current Murine Models Used in Antimalarial Drug Discovery

Most murine strains used in malaria research are inbred strains. The reason for using inbred strains is the uniformity obtained from individual experimental outcomes, especially in antimalarial drug discovery [44,45]. Overcoming some of the phylogenetic distance between mice and humans is the rationale for using humanized mouse strains [32].
Mice are either susceptible or resistant to Plasmodium infections. Their resistance may indicate non-lethality of the parasite to mice or late mortality [46]. Screening of novel compounds that consider the fatality of cerebral malaria also requires the use of murine models susceptible to cerebral malaria pathogenesis [47]. Different mouse strains important to antimalarial drug discovery are highlighted in this review.

2.1. A Summary of the Various Inbred Mice That Have Been Used and Their Strengths and Weaknesses

Various inbred strains of mice have been used in malaria research. Plasmodium-infected Bagg Albino c (BALB/c) mice are widely used in malaria research. Some of such studies include understanding the gut microbiome and its relationship with malaria pathogenesis, vaccine development, the discovery of new chemical entities in ethnomedicine, and more [48,49,50]. BALB/c mice are photophobic and possess a lengthy reproductive threshold [51,52]. Mortality in these mice is delayed until high parasitemia is reached, and they are resistant to cerebral malaria [32,53]. These mice can be infected with the different rodent Plasmodium species and can be used in efficacy studies of new chemical entities for antimalarial drug discovery (Table 2). BALB/c mice show anxiety, depression, and aggression naturally. Their immune system is not a representation of the human immune system [54].
AKR/J inbred mice are resistant to P. berghei infection; therefore, they are rarely considered as models for in vivo antimalarial efficacy testing in drug discovery [55,56]. This mouse strain displays resistance to cerebral malaria due to its deficiency in the complement component C5 [57]. Nevertheless, AKR/J mice have better visual capacity than other albino mice despite aging [58].
C3H/HeJ mice are an immunocompetent inbred strain susceptible to both P. berghei and P. chabaudi malaria. They have displayed reduced responses to chloroquine treatment but efficacious responses to dihydrotriazines and biguanides in the treatment of babesiosis and malaria [59,60,61]. This strain of mice is more commonly associated as a model for babesia research than malaria [62]. C3H/HeJ mice possess immunosuppressive capacity; therefore, their disease severity is low [63].
CBA mice are an inbred strain susceptible to P. berghei infection. They are commonly used as a model for cerebral malaria because they are genetically predisposed to it at hypoparasitemic conditions even when infected with other rodent strains including P. chabaudi and P. yoelii [55,64]. CBA mice possess a homogenous genetic characteristic and uniformity in their response physiologically. They have a short life-span (6 months) due to an inherited foam cell reticulosis [65].
SJL/J is an inbred mouse strain susceptible to P. berghei and P. chabaudi. P. berghei infection may lead to severe malaria and, consequently, cerebral malaria but in an asymptomatic condition [47,66]. This strain may be considered as a murine model for the screening of lead compounds in antimalarial drug discovery. SJL/J is resistant to Cryptococcus infection. Despite this, this mouse strain can briefly represent malaria disease states in humans.
C57BL/6 mice are commonly used inbred strains in antimalarial drug discovery programs. They have a competent immune system, and they are also called ‘B6” [54,67,68,69]. C57BL/6 mice were successfully inoculated with P. falciparum. Hence, they are recommended for use in antimalarial drug discovery [67]. They are also widely used as a model of human cerebral malaria and immunological responses to malaria. They are resistant to P. chabaudi malaria [32,70,71,72]. Nevertheless, similarities occur between the diseased (C57BL/6) mice model infected with Plasmodium berghei ANKA and the human disease [73]. Essentially, sequestration of P. berghei occurs in the brain of the rodent as a similar condition occurs during pathogenesis in the human disease [73].
DBA/2J mice are inbred strains rarely used as models in antimalarial drug testing, but they have been explored for neurological experiments. However, they are resistant to cerebral malaria but susceptible to P. berghei infection [53,55,59,74]. This mouse strain has also been infected with other rodent parasite strains, including P. yoelii, P. chabaudi, and P. vinckei, making it suitable for drug screening [55,59]. DBA/2J mice display some heterogeneity in their genetic constitution [75].

2.2. Outbred Mice

Swiss Webster is a widely used outbred mouse susceptible to P. berghei, P. chabaudi, and P. yoelii infection and is currently still used in the determination of the in vivo efficacy of new chemical entities [76]. This outbred strain also manifests cerebral malaria in severe parasitemia cases, which is also considered in treatment development [77]. Transgenic parasite lines of P. berghei have also been explored in this mouse model [78].
The Institute of Cancer Research (ICR) mice are outbred and highly susceptible to P. chabaudi infection as they are to P. berghei [72,79]. They are commonly used as a model for the in vivo screening of potential antimalarial molecules obtained from plant sources [80,81,82]. These mice also manifest cerebral malaria in severe cases [47].
CD1 mice are Swiss-based outbred strains susceptible to multiple rodent Plasmodium species [12]. This mouse strain is employed to evaluate the pharmacokinetic properties and the safety of novel compounds [12,83].
Naval Medical Research Institute (NMRI) mice are outbred strains susceptible to P. berghei infection [84,85]. In NMRI mice, P. berghei parasite development occurs exponentially. Therefore, the efficacy of new chemical entities can be estimated suitably in this mouse model [85]. Hepatic-stage Plasmodium infection is also assessed using this model, which could mean the inoculation of transgenic parasites [86]. NMRI mice are also models for cerebral malaria pathogenesis from P. berghei or P. yoelii infection [47].

2.3. Humanized Mice

Humanized mice are now the order of the day in antimalarial drug discovery. They are engrafted with human cells under immunocompromised conditions while also knocking in human genes into the mouse genomes, thereby more effectively representing human parasite pathogenesis for treatment purposes [87]. Although non-humanized mouse models have aided in successful human predictions of the efficacy of new chemical entities and their pharmacokinetics in antimalarial drug discovery, there are certain advantages and disadvantages to using them (Table 3) [73].
NOD/SCID/gamma (c) (null), known as NOG mice, are immunocompromised and void of essential lymphocytes like B and T cells although macrophages remain present [88]. Meanwhile, macrophages have emerged as critical natural protective agents in malaria pathogenesis in humans, which can now be assessed in this mouse strain [89]. These human model mice can be infected with human Plasmodium parasites for novel therapeutic studies, as well as the evaluation of pharmacological parameters [90].
NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mouse strain, similar to NOG, is susceptible to both P. falciparum and Plasmodium vivax. It is helpful for the efficacy determination of new chemical entities against P. falciparum. Efficacy can also be evaluated against liver-stage hypnozoites characterized by P. vivax infection [91,92].
The FRG NOD huHep mouse is a model for the human chimeric liver in P. falciparum malaria research. It has aided the understanding of P. falciparum pathology transiting from hepatic- to erythrocytic-stage development, which presents a platform for novel antimalarial screening [93].
5xFAD mice are a transgenic mouse model that is predisposed to Alzheimer’s disease and they are characterized by the presence of some amyloid plaques [94]. Cerebral malaria has been hypothesized to be associated with apolipoprotein-mediated amyloidosis, whose pathogenicity may also be observed in Alzheimer’s disease [95]. Elevated levels of apolipoprotein are observed in the mouse brain during cerebral malaria pathogenesis, which could result in neurological dysfunction, as was observed in mice [95]. Artesunate is reported to alleviate the amyloidosis pathology in 5xFAD mice [96]. This suggests that 5xFAD mice could be explored for antimalarial drug development in treating cerebral malaria.
A future perspective of murine models in antimalarial drug discovery is that although humanized mice have been able to recapitulate the malarial efficacy in humans, the extrapolation of pharmacokinetic responses from mice to humans needs to be clearly understood for all drugs and their mechanism of action [97]. This means that we need to know if every antimalarial can clearly represent the pharmacokinetic parameters in humans, using humanized mice [97].
Table 2. Murine strains used in antimalarial drug discovery.
Table 2. Murine strains used in antimalarial drug discovery.
Murine ModelTypePreclinical Assays ConductedResistant/Susceptible to P. bergheiPlasmodium Species AssessedReferences
BALB/cInbredEfficacy, Pharmacokinetics, Safety,SusceptibleP. yoelii,
P. chabaudi,
P. vinckei
[46,50,59,98,99,100]
AKR/JInbredPharmacokineticsResistant-[58,59]
C3H/HeJInbredEfficacySusceptibleP. chabaudi[59,61,63]
CBAInbredEfficacySusceptible P. yoelii,
P. chabaudi,
P. vinckei
[55,64,65,101,102]
SJL/JInbred SusceptibleP. chabaudi[59,66,103]
C57Bl/6InbredEfficacy,
Safety
SusceptibleP. yoelii,
P. chabaudi P. falciparum,
P. vinckei
[32,55,70,71,72].
DBA/2JInbred ResistantP. yoelii,
P. chabaudi,
P. vinckei,
[75,104,105,106,107,108]
Swiss WebsterOutbredEfficacy,
Toxicity
Susceptible
P. yoelii
P. chabaudi
[109,110,111,112,113]
ICROutbredEfficacy,
Pharmacokinetics,
Safety
SusceptibleP. yoelii,
P. chabaudi, P. vinckei
[12,114,115,116,117]
CD1OutbredEfficacy,
Pharmacokinetics,
Safety
SusceptibleP. chabaudi, P. yoelii[47,84,85,86,118]
NMRIOutbred Efficacy, Pharmacokinetics,
Safety
Susceptible P. chabaudi, P. yoelii[90,119,120,121,122]
NOD/SCID/γcnull (NOG)HumanizedEfficacy,
Pharmacokinetics
P. falciparum[91,92,104]
NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJHumanizedEfficacy,
Pharmacokinetics
P. falciparum, P. vivax[123,124]
FRG NOD huHep HumanizedEfficacy P. falciparum[96]
5xFADTransgenic---
Table 3. Advantages and disadvantages of using non-humanized and humanized mouse models in antimalarial drug discovery.
Table 3. Advantages and disadvantages of using non-humanized and humanized mouse models in antimalarial drug discovery.
Advantages of Using Non-Humanized Mouse Models in Antimalarial Drug DiscoveryDisadvantages of Non-Humanized Mice Models in Antimalarial Drug DiscoveryAdvantages of Humanized Mice Models in Antimalarial Drug DiscoveryDisadvantages of Humanized Mice Models in Malaria Research
Despite the challenge of an unclear representation of the human immune system in mice, basic immunological responses have been used to give reliable results of predicted failures in malarial vaccine development [73]. Immunology in non-humanized mice is not a clear representation of human immunology [73].Enhancement of potential antimalarial efficacy studies has been granted through the use of humanized mice models [125].Mouse innate immunity is difficult to reduce to increase human adaptive immunity [126].
Gaining insight into cerebral malaria is technically challenging due to the inaccessibility of the human brain tissue. Pharmacodynamic/pharmacokinetic studies of novel compounds can be conducted to obtain a representation of what could be obtained in humans [125].It is challenging to engraft human cells into mice while generating humanized mice [127].

3. In Vivo Pharmacokinetic (PK) Studies

Several factors, including excellent pharmacokinetic properties, increased half-life, and appropriate metabolic distribution, can influence the potency of a compound [128]. Pharmacokinetic properties such as in vivo bioavailability are considered a significant complement to the in vitro efficacy assessment in the identification of new leads in antimalarial drug discovery [129] (Figure 2). Drug metabolism and pharmacokinetic (DMPK) profiling is essential to the optimization of potent compounds in the antimalarial drug development program, and it determines how far these compounds can traverse the drug discovery pipeline [130]. DMPK profiling involves both in vitro and in vivo experiments. In vitro experiments require the use of cells in a controlled environment, but in vivo experiments require the use of animal models, of which murine models are critical [130].

3.1. Oral Bioavailability

In vivo, oral bioavailability of drugs is associated with oral absorption, and oral bioavailability in rodent models may be used predict that in humans [131,132]. Oral bioavailability is the percentage of administered test compound that ends up in the bloodstream (Figure 3). In contrast, oral absorption is the amount of test compound taken up by the gastrointestinal system [132,133]. Oral bioavailability influences the decision on the drug exposure and dosage regimen of test compounds. Low oral bioavailability may lead to the failure of lead compounds despite in vitro potency, which must be prevented in clinical trials to avoid the wastage of resources [134,135]. Although several in silico tools have been designed to predict oral bioavailability, they do not always correlate with actual in vivo experiments [132,134]. Nevertheless, predictive tools can guide the decision processes for potent test compounds’ experimental oral bioavailability determination that should be selected as acceptable lead compounds [132,134]. In vivo, oral bioavailability is usually estimated from calculations after the experiment has been conducted in rodent models using high-performance liquid chromatography–electrospray ionization–tandem mass spectrometry (HPLC-ESI-MS/MS) [132,136]. The oral bioavailability of a test compound can be elevated by increasing the solubility and reducing the compound’s melting point [135,136,137]. Excellent oral bioavailability represents good drug gastrointestinal permeability and absorption [135,136].
In the selection process of potent hits traveling from phenotypic screening, it is of essence to first consider their in vivo pharmacokinetic profile [138]. If the pharmacokinetic properties are undesirable due to challenges occurring from oral bioavailability, other routes of administration are best employed, such as the intravenous route [138].
Oral bioavailability is associated with the oral absorption of the test compounds. Drug distribution profiling evaluates how the test compounds travel the systemic circulation. Metabolic stability is a measure of the metabolic rate of the test compounds in the liver. Drug clearance and excretion describes the elimination rate of the test compound from the liver.

3.2. Drug Distribution Profiling

In vivo, drug distribution is determined by evaluating how barriers such as the blood–brain barrier (BBB) are penetrated and how the volume of compounds that traverse the membrane to reach their target is measured with respect to plasma protein binding (PPB) [139,140]. Drug distribution is a reversible process in pharmacokinetic profiling that begins with the process of drug dilution to plasma binding through absorption, and then drug molecules are dispersed to other parts (Figure 3) [141].
The volume of distribution (Vd) of a test compound is the apparent volume of the test compound in plasma and it measures the extent of distribution of the compound [138,142,143]. The Vd is very important because it influences the half-life of the test compound as well as the dosage frequency [142]. When the Vd of a test compound is low, the half-life of that compound will be low [144]. The apparent volume of distribution of a test compound is a required pharmacokinetic property when a decision is to be made on the choice of lead compounds, especially if they are considered in combination with other compounds or existing antimalarials such as artemisinin-based treatment [139,145,146]. The apparent volume of distribution is usually determined after intravenous administration [147,148]. Dosage optimization of drugs is also influenced by the Vd, among other pharmacokinetic parameters [149].
Drugs or test compounds are either bound to plasma proteins or lipids or unbound. When bound in the blood, they are bound to proteins and lipid molecules, hence called plasma protein binding (PPB) [150]. Determining PPB for lead compounds is critical to inform further decisions in the drug development pipeline. If it is reversible, PPB does not influence the efficacy of the test compound in vivo [151,152]. High PPB means that the apparent volume of distribution and lipophilicity is high. Still, the elimination of the test compound is reduced, which is advantageous in the context of the extended half-life [141,153,154,155]. The increased half-life of lead compounds may be traced to high PPB. It influences the raising of the apparent volume of distribution and may prosper the course of a single-dose regimen of the lead compound being validated in vivo [154]. PPB can be assessed in vivo in rodents using ultracentrifugation or equilibrium dialysis [154,156].
Albumin and alpha-1-acid glycoprotein (AAG) are two common plasma proteins measured when evaluating the PPB property of a test compound [144,155]. Both plasma proteins are produced in the liver, and plasma albumin exists in higher concentrations than plasma AAG. Abnormal physiological conditions, therefore, alter the functioning of these plasma proteins [153,155]. Albumin in plasma binds to both acidic and basic compounds. Meanwhile, AAG binds to more basic, neutral lead compounds [153]. It is worth noting that children and pregnant women display reduced levels of plasma protein binding to albumin. Therefore, the apparent volume of distribution will be reduced, and this should be considered in the drug development plan for neonates [149,153,157].

BBB Dysfunction and Cerebral Malaria

BBB penetration is an important in vivo pharmacokinetic parameter for consideration during antimalarial drug development. BBB penetration is a parameter for the representation of the drug distribution profile of test compounds [140,158]. It is a measure of the concentration of test compounds present in the brain against the concentration found in the blood [140]. BBB is of particular interest when treating cerebral malaria. A dysfunctional BBB is significantly associated with cerebral malaria [159]. Plasmodium parasites compromise the BBB, leading to neurological dysfunction. Certain markers that escape through the compromised BBB can be traced when found in the blood, for instance, the “tau” protein [160]. Experimental cerebral malaria thrives in murine models on the basis that infected erythrocytes are amassed in the brain’s vascular system [161]. Artesunate is currently recommended as a treatment for cerebral malaria in the current mouse model (C57BL/6) used for cerebral malaria infected with P. berghei. [162,163]. In vivo BBB integrity is determined through spectrophotometry, having extracted the brain from experimental mice injected with Evans blue [159,162]. Intravenous administration of lipid-carrying potential drug molecules could elevate BBB integrity [163]. Intranasal delivery of nanostructured lipid carriers has also been reported to effectively traverse the blood–brain barrier for treatment for cerebral malaria [163,164].

3.3. Metabolic Stability

Microsomal stability assay is a test conducted to evaluate the metabolism rate of lead compounds undergoing optimization. It measures the metabolic stability of the test compounds in both in vitro and in vivo hepatocytes [165]. The metabolism of test molecules is usually a function of hepatic processes facilitated by liver cytochrome enzymes [166].
Microsomes possess cytochrome P450 enzymes and enzymes like uridine 5′-diphospho-glucuronosyltransferase that metabolize most antimalarials in mice liver [109,167]. Microsomal stability of several potential antimalarials has been tested in rats, mice, dogs, and human microsomes [68,168]. The metabolic rate of microsomal enzymes in Plasmodium-infected mice is reported to be lower than in the uninfected counterparts, and the measurement of how low this clearance would be is yet unclear [109]. Metabolic stability is measured as a function of the half-life of the test compounds, the level of liver microsome proteins present, and the intrinsic clearance (in vitro) [109,168]. The half-life is the removal of 50% of the test compound, while intrinsic clearance describes the hepatic activity (as a function of the microsome protein content) against the test compound minus the influence of other hepatic factors such as the blood flow in the liver [169]. During the assay, samples of the test compound in the presence of extracted liver microsomes are collected at different time points for the estimation of intrinsic clearance [170]. Increased clearance rates insinuate decreased half-lives of the test compounds in the liver, indicating a large volume of drug distribution [168,171]. Microsome stability assays are evaluated for blood-stage, liver-stage, and transmission-blocking potential antimalarials [172,173,174,175]. Lead compounds displaying excellent metabolic stability proceed further in the antimalarial drug development pipeline [175]. In vitro microsomal stability assays are conducted more frequently than in vivo microsomal assays in antimalarial drug development [170,172,173,174,175,176].

3.4. Drug Clearance and Excretion

The rate at which a test compound is eliminated from the animal describes excretion. Meanwhile, the total clearance involves the disappearance of the drug molecules from the plasma–compound-bound complex at a given time [177]. The metabolic activities in the liver and kidney marshal this plasma clearance (Figure 3). Clearance from the liver is termed ‘hepatic intrinsic clearance’, and from the kidney, it is called ‘renal clearance’ [9,166]. In vitro, hepatic intrinsic clearance of free unbound molecules is evaluated using liver microsomes. High intrinsic clearance is directly proportional to a rise in the octanol/pH 7.4 buffer partition coefficient. The partition coefficient is the distribution of a solute’s concentration between the oil and water phases [178]. Reduced levels of intrinsic clearance of unbound molecules increase the half-life of the molecules [154,166]. This intrinsic clearance provides a basis for the prediction of the in vivo total clearance of the test molecule [166]. Data generated from the in vitro hepatic intrinsic clearance are used to make predictions for the in vivo hepatic intrinsic clearance. The transition from in vitro to in vivo hepatic intrinsic clearance requires the use of scaling factors that consider the weight of the in vivo mammalian species to be used [166].
The excretion of compounds undergoing optimization as a pharmacokinetic property incorporates the half-life or elimination of the drug in vivo [177]. Elimination of a test compound is the permanent removal of the compound from systemic circulation [179]. Renal excretion provides the means for eliminating unbound test molecules and can be evaluated in vivo in rodent models [68]. Renal clearance is facilitated by glomerular filtration and active transport (both can be extrapolated using the rodent model for evaluation) [180].

4. In Vivo Safety Studies

Toxicity outcomes of the potent molecules must be considered at an early stage of the drug discovery program using preclinical testing such as mouse models [125] (Figure 4). Hewitt et al. [125] provided a guideline for safety tests to be conducted on lead compounds in vivo before further drug development. Some in vivo toxicity assays include cardiotoxicity, genotoxicity, phototoxic potential, Good Laboratory Practice (GLP) toxicology studies, combination toxicity studies, cumulative exposure studies, and developmental and reproductive toxicology testing [5,125,181].

4.1. Cardiotoxicity (hERG)

Cardiotoxicity as a detrimental side effect has been associated with certain classes of antimalarials, including quinolines. This is a critical subject as new molecules are being investigated for antimalaria development [182,183]. At an early stage of preclinical studies, assessing the toxic effects of lead compounds on cardiomyocytes is recommended (World Health Organization) for investigation with measurements of the molecular marker human ether-ago-go-related gene (hERG) [5,125,182,183]. Siqueira-Neto et al. [5] recommend an absence of toxicity against hERG at 1 µM during the early stage of preclinical tests. Meanwhile, at the late stage, the threshold for hERG toxicity must be further reduced when evaluated in vivo. In vivo, cardiotoxicity of antimalarials and potential antimalarials have been determined in rats and zebrafish [183,184].

4.2. Genotoxicity

Genotoxicity assays are designed to measure the level of genetic damage conferred by a test molecule, and the odds of the damage caused are at risk of transmission from one generation to another. There are both in vitro and in vivo assays conducted to determine the genotoxic status [185,186]. It is essential to conduct in vivo genotoxicity experiments in addition to in vitro experiments in order to obtain reliable results [186]. Drug candidates with genotoxic potential are excluded during early preclinical screening [186,187]. In vivo genotoxicity has been conducted in rodent models and dogs in the early stages of antimalarial drug discovery [181,188]. Carcinogenicity studies are not considered during antimalarial drug discovery because the dosage regimen is for a short period [125].

4.3. Phototoxicity

Phototoxicity occurs when undesirable skin responses are observed after administering a drug candidate or a test molecule [189,190]. The phototoxic potential of antimalarial drug candidates has recently been considered for assessment during an early preclinical phase. This test is also conducted in vivo [5,125,191]. In phototoxicity testing, mice are treated with test compounds by oral administration, after which the mice are irradiated with ultraviolet light, which is a simulation of sunlight. Phototoxic reactions are then observed [192]. For instance, compounds with the best potencies displayed phototoxicity while the Second World War was in progress, which led to halting the compounds’ development [146]. Pyrimethamine monotherapy is reported to display phototoxicity in humans when exposed to ultraviolet A or B light, which results in damaged cells [193].

4.4. Good Laboratory Practice (GLP) Toxicology Studies

Good Laboratory Practice (GLP) toxicology assessment is a regulatory laboratory procedure conducted in vivo (in rodents and dogs) for 2 weeks [125,194]. This toxicity study is a dose range-finding experiment in rodents to determine how harmful specific concentrations of the lead molecule will be according to GLP standards [195]. One frequently used method is the maximum tolerated dose (MTD) approach, which assesses the toxicity and dose range of the potential drug compound [195,196]. GLP procedures are primarily non-clinical studies conducted before clinical studies in drug development [125,195].

4.5. Combination Toxicity Studies

Combination therapy in antimalarial drug development is critical to the elimination of malaria due to the challenge of monotherapy resistance [197,198]. In the process of discovering new drug combinations of excellent efficacies, the combination of compounds must not increase the toxicity [199]. Combination toxicity is a non-clinical study conducted for about three months using rodents. Each compound is evaluated individually (and in combination), especially when each compound is exclusively efficacious as a requirement for the combination of test compounds used [200].

4.6. Repeated-Dose Toxicity

A repeated-dose toxicology (RDT) study is a non-clinical approach to evaluating the toxicity of the test compounds to determine safety [201]. RDT for potential antimalarials is determined in both rodent and non-rodent species, but particularly in rats, usually for a period of 14 days, where the test compound is administered for all the days [125,202,203]. RDT is a significant testing approach for new chemical entities that are not administered as a single dose, and side effects of the test compounds are sufficiently estimated before further development while considering test compounds with increased half-lives [125,204].

4.7. Developmental and Reproductive Toxicity Testing

Developmental and reproductive toxicology is paramount in considering lead compounds that should proceed for further development [205,206,207]. Development and reproductive toxicological studies are preclinical studies conducted to determine the test compound’s embryotoxic or teratogenic effects in vivo, informing the decisions of choice and how to improve the selected lead compounds [5,205,206,208]. Artemisinin displayed embryotoxicity in the first three months in pregnant women [205]. This was observed to be as a result of the time of administration of the compound and the dosage involved. It was, therefore, suggested that women in their first trimester of pregnancy should desist from the use of artemisinin-based therapy [205].

5. In Vivo Rodent Efficacy Studies

In vivo, efficacy testing in antimalarial drug discovery is an indispensable aspect of the development pipeline (Figure 5) [209]. The potency of lead compounds is evaluated at different developmental stages of the parasite in vivo [5]. Rodents are the face of preclinical efficacy testing in antimalarial discovery, following validations from in vitro screenings and the identification of lead compounds [71]. During efficacy studies, rodent models are selected based on the class of antimalarial candidate being evaluated or the type of population the drug is designed for [209].
Rodent models are amenable to several routes of drug administration. Routes of administration of drug treatments include oral, rectal, intramuscular, intravenous, and subcutaneous. Other routes of administration aside from oral dosage are explored when test compounds are not quickly soluble [129]. The oral route of administration is most common in antimalarial drug discovery and does not require any technical skills. The compound administered essentially undergoes absorption in the small intestine [5,210]. Rectal administration occurs by using the rectum as a route for the drugs; absorption occurs in the rectum and travels to the level [210]. Artesunate has been administered rectally in the case of severe malaria [5]. Intravenous administration occurs by using injection, and compounds can travel through the systemic circulation through the veins [210]. The subcutaneous route of administration is an entry of the drug through the skin, which is also applied through injections at the thigh or buttocks. Drugs are absorbed slowly but sustainably [210]. When compounds are administered through the intravenous or subcutaneous route, Plasmodium sporozoites are targeted for clearance [5]. The intramuscular route of administration involves entry through muscles by injections. It requires the technicality of experts and, therefore, should be handled with care [210]. Arteether is administered intramuscularly in the case of severe malaria [211].

5.1. Prophylactic Test

A test compound’s prophylactic efficacy is the capacity to prevent the development of the Plasmodium parasite, thereby preventing the progression of the parasite’s pathological cycle [212,213]. Prophylactic treatment is administered chiefly to travelers and migrants to and from malaria-endemic countries [212]. In vivo prophylactic test is an immediate efficacy evaluation to be conducted, having pinpointed the lead compound [214]. To evaluate prophylaxis, rodents are initially administered the test compound and inoculated with the rodent Plasmodium parasite afterward. The efficacious activity of the test compound is measured by the level of parasite densities or parasitemia at the end of the experiment [215,216]. Lead compounds may be evaluated for their prophylactic efficacy by hindering the parasite development at the pre-erythrocytic/hepatic (causal) or erythrocytic (suppressive) stage [213,217]. Suppressive treatment inhibits erythrocytic-stage parasitic infections [218].

5.2. Suppressive Test

The most prevalent in vivo chemo-suppression assay is Peter’s four-day suppressive test, which entails a four-day treatment procedure a few hours after parasite inoculation [71,215]. Mean survival time is also determined during Peter’s suppressive test, which estimates how long the animals survive post-treatment [219]. Parasitemia and percentage suppression are determined from the experiments as a measure of chemo-suppression [215].

5.3. Curative Test

Rane’s test is the most widely used to assess the curative efficacy of new chemical entities in vivo [215,220]. During this experiment, treatment of the animals inoculated with the rodent Plasmodium parasite begins from day 3 post-infection and lasts for 4 days. Curative treatment is usually administered orally, intraperitoneally, and through other avenues [220]. Curative tests conducted for lead molecules are particularly essential when treating cerebral malaria [220,221].

5.4. Parasite Viability

In vivo parasite viability estimation post-treatment has been considered a more informative measure of drug efficacy than just the number of parasites or strength of a reporter signal [222]. Analogous to the concept of colony-forming units in virology, this method uses limiting dilution and in vitro regrowth to determine the number of viable parasites after drug wash out. While this is very laborious and time-consuming, it aids in measuring the lead compound’s cidal effect and the maximal concentration to obtain the optimal cidal effect [222]. Parasite viability as a read-out can correct for underestimation of a drug’s efficacy. For example, artesunate appeared to leave some parasites in circulation after treatment [222]. Nevertheless, these were not actually viable and over-estimation of efficacy was observed with a P. falciparum field isolate that appeared to respond to piperaquine but actually would not be cleared by it [223].

5.5. Examples of Antimalarial Lead Compounds and the In Vivo Efficacy Assessment Conducted

Some antimalarial leads have demonstrated promising in vivo efficacy, particularly in curative and survivability tests. Some are listed in Table 4.

5.6. Limitations to Using Murine Models in Antimalarial Drug Discovery

Phenotypic expressions of malaria are heterogeneous across the different mouse strains. Therefore, it is still unknown which mouse strain manifests the disease best comparable to the human disease [73]. Therefore, it is encouraged that mouse models clearly represent the human disease state [73]. Murine models have been used to predict failed vaccines at the preliminary stage, where these vaccine tests are not always successful [73]. Drugs that lead to anemic consequences in humans do not cause anemia in non-humanized mice during antimalaria treatment [232]. Malaria infection in murine models reduces the integrity of cytochrome P450’s activity in drug metabolism [233]. While conducting in vivo experiments in murine models, the amount of test compound needed is high, which may practically be challenging when applied in human studies [234]. The extrapolation of analyzed results from tests against Plasmodium berghei to the human parasite [234].

6. Conclusions

Careful selection of lead molecules in preclinical studies is critical to minimizing failures in later clinical trials, where discrepancies between murine and human responses often arise. Therefore, the availability of murine resources in in vivo validation experiments of in vitro-identified lead compounds provides a rich basis for assessing these new chemical entities for their safety, toxicity, dosage regimen, and efficacy in preclinical trials. This informs the Phase I clinical trials and can reduce the risk of failures during clinical trials. Moreover, murine models are beneficial for understanding other malaria-associated bioactivities, for instance, vaccine development, metabolic responses during the disease cycle, and more. These contribute to the malaria control efforts from a broader perspective. In view of this broader perspective, more development in engineering mice towards understanding the disease condition wholly is necessary.

Author Contributions

Conceptualization, G.A., G.O. and E.A.; resources, O.O.A., O.I.A., O.S.A., E.A., M.R. and O.A.; writing—original draft preparation, G.A.; writing—review and editing, G.A., G.O., J.M., O.S.A., P.M. and E.A.; supervision, O.I.A. and E.A.; funding acquisition, O.O.A. and E.A. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the NIH grant number U2RTW010679, through Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria.

Data Availability Statement

Not applicable.

Acknowledgments

Our appreciation goes to the staff of Covenant University Bioinformatics Research (CUBRe), and the Department of Biochemistry Nigerian Institute of Medical Research (NIMR), for providing support towards this review. We also appreciate Yagoub Adam and Oluwafunminiyi Obaleye for their support. Authors also acknowledge the logistical support of Babajide Ayodele. Covenant University provided the infrastructural support.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AAG Albumin and alpha-1-acid glycoprotein
BALB/cBagg Albino
BBBBlood–brain barrier
GLPGood Laboratory Practice
hERGhuman ether-ago-go-related gene
HPLC-ESI-MS/MShigh-performance liquid chromatography–electrospray ionization–tandem mass spectrometry
ICRInstitute of Cancer Research
PPBPlasma protein binding
PKPharmacokinetic
RDTRepeat-dose toxicology
TOTheiler’s Original
VdVolume of distribution

References

  1. Lindblade, K.A.; Hong, L.X.; Tiffany, A.; Galappaththy, G.; Alonso, P.; Abeyasinghe, R.; Akpaka, K.; Aragon-Lopez, M.A.; Baba, E.S.; Bahena, A.; et al. Supporting Countries to Achieve Their Malaria Elimination Goals: The WHO E-2020 Initiative. Malar. J. 2021, 20, 481. [Google Scholar] [CrossRef]
  2. Hemingway, J.; Shretta, R.; Wells, T.N.C.; Bell, D.; Djimdé, A.A.; Achee, N.; Qi, G. Tools and Strategies for Malaria Control and Elimination: What Do We Need to Achieve a Grand Convergence in Malaria? PLoS Biol. 2016, 14, e1002380. [Google Scholar] [CrossRef] [PubMed]
  3. Pandey, S.K.; Anand, U.; Siddiqui, W.A.; Tripathi, R. Drug Development Strategies for Malaria: With the Hope for New Antimalarial Drug Discovery—An Update. Adv. Med. 2023, 2023, 5060665. [Google Scholar] [CrossRef]
  4. Dhameliya, T.M.; Kathuria, D.; Patel, T.M.; Dave, B.P.; Chaudhari, A.Z.; Vekariya, D.D. A Quinquennial Review on Recent Advancements and Developments in Search of Anti-Malarial Agents. Curr. Top. Med. Chem. 2023, 23, 753–790. [Google Scholar] [CrossRef]
  5. Siqueira-Neto, J.L.; Wicht, K.J.; Chibale, K.; Burrows, J.N.; Fidock, D.A.; Winzeler, E.A. Antimalarial Drug Discovery: Progress and Approaches. Nat. Rev. Drug Discov. 2023, 22, 807–826, Corrected in Nat. Rev. Drug Discov. 2024, 23, 880. [Google Scholar] [CrossRef]
  6. Singh, A.P.; Rathi, B. Editorial: Advances in Anti-Malarial Drug Discovery. Front. Drug Discov. 2023, 3, 1335842. [Google Scholar] [CrossRef]
  7. Rao, S.P.S.; Manjunatha, U.H.; Mikolajczak, S.; Ashigbie, P.G.; Diagana, T.T. Drug Discovery for Parasitic Diseases: Powered by Technology, Enabled by Pharmacology, Informed by Clinical Science. Trends Parasitol. 2023, 39, 260–271. [Google Scholar] [CrossRef]
  8. Ncube, N.B.; Tukulula, M.; Govender, K.G. Leveraging Computational Tools to Combat Malaria: Assessment and Development of New Therapeutics. J. Cheminform. 2024, 16, 50. [Google Scholar] [CrossRef]
  9. Akash, S.; Abdelkrim, G.; Bayil, I.; Hosen, M.E.; Mukerjee, N.; Shater, A.F.; Saleh, F.M.; Albadrani, G.M.; Al-Ghadi, M.Q.; Abdel-Daim, M.M.; et al. Antimalarial Drug Discovery against Malaria Parasites through Haplopine Modification: An Advanced Computational Approach. J. Cell. Mol. Med. 2023, 27, 3168–3188. [Google Scholar] [CrossRef]
  10. Duay, S.S.; Yap, R.C.Y.; Gaitano, A.L.; Santos, J.A.A.; Macalino, S.J.Y. Roles of Virtual Screening and Molecular Dynamics Simulations in Discovering and Understanding Antimalarial Drugs. Int. J. Mol. Sci. 2023, 24, 9289. [Google Scholar] [CrossRef]
  11. Tisnerat, C.; Dassonville-Klimpt, A.; Gosselet, F.; Sonnet, P. Antimalarial Drug Discovery: From Quinine to the Most Recent Promising Clinical Drug Candidates. Curr. Med. Chem. 2022, 29, 3326–3365. [Google Scholar] [CrossRef]
  12. Peric, M.; Pešić, D.; Alihodžić, S.; Fajdetić, A.; Herreros, E.; Gamo, F.J.; Angulo-Barturen, I.; Jiménez-Díaz, M.B.; Ferrer-Bazaga, S.; Martínez, M.S.; et al. A Novel Class of Fast-acting Antimalarial Agents: Substituted 15-membered Azalides. Br. J. Pharmacol. 2021, 178, 363–377. [Google Scholar] [CrossRef]
  13. Jiménez-Díaz, M.B.; Viera, S.; Fernández-Alvaro, E.; Angulo-Barturen, I. Animal Models of Efficacy to Accelerate Drug Discovery in Malaria. Parasitology 2014, 141, 93–103. [Google Scholar] [CrossRef] [PubMed]
  14. Ingber, D.E. Human Organs-on-Chips for Disease Modelling, Drug Development and Personalized Medicine. Nat. Rev. Genet. 2022, 23, 467–491. [Google Scholar] [CrossRef]
  15. Cauvin, A.J.; Peters, C.; Brennan, F. Advantages and Limitations of Commonly Used Nonhuman Primate Species in Research and Development of Biopharmaceuticals. In The Nonhuman Primate in Nonclinical Drug Development and Safety Assessment; Elsevier: Amsterdam, The Netherlands, 2015; pp. 379–395. [Google Scholar]
  16. McCallum, F.J.; Birrell, G.W.; Chavchich, M.; Harris, I.; Obaldia, N.; Van Breda, K.; Heffernan, G.D.; Jacobus, D.P.; Shanks, D.; Edstein, M.D. In Vivo Efficacy and Pharmacokinetics of the 2-Aminomethylphenol Antimalarial JPC-3210 in the Aotus Monkey-Human Malaria Model. Antimicrob. Agents Chemother. 2020, 64. [Google Scholar] [CrossRef]
  17. Ramanathan-Girish, S.; Catz, P.; Creek, M.R.; Wu, B.; Thomas, D.; Krogstad, D.J.; De, D.; Mirsalis, J.C.; Green, C.E. Pharmacokinetics of the Antimalarial Drug, AQ-13, in Rats and Cynomolgus Macaques. Int. J. Toxicol. 2004, 23, 179–189. [Google Scholar] [CrossRef]
  18. Duffy, P.E. Current Approaches to Malaria Vaccines. Curr. Opin. Microbiol. 2022, 70, 102227. [Google Scholar] [CrossRef]
  19. Luo, K.; Gordy, J.T.; Zavala, F.; Markham, R.B. A Chemokine-Fusion Vaccine Targeting Immature Dendritic Cells Elicits Elevated Antibody Responses to Malaria Sporozoites in Infant Macaques. Sci. Rep. 2021, 11, 1220. [Google Scholar] [CrossRef]
  20. Gupta, A.; Styczynski, M.P.; Galinski, M.R.; Voit, E.O.; Fonseca, L.L. Dramatic Transcriptomic Differences in Macaca Mulatta and Macaca Fascicularis with Plasmodium Knowlesi Infections. Sci. Rep. 2021, 11, 19519. [Google Scholar] [CrossRef]
  21. Martini, J.; Gramaglia, I.; Intaglietta, M.; van der Heyde, H.C. Impairment of Functional Capillary Density but Not Oxygen Delivery in the Hamster Window Chamber during Severe Experimental Malaria. Am. J. Pathol. 2007, 170, 505–517. [Google Scholar] [CrossRef]
  22. Miao, J.; Chard, L.S.; Wang, Z.; Wang, Y. Syrian Hamster as an Animal Model for the Study on Infectious Diseases. Front. Immunol. 2019, 10, 2329. [Google Scholar] [CrossRef]
  23. Mossallam, S.F.; Amer, E.I.; El-Faham, M.H. Efficacy of SynriamTM, a New Antimalarial Combination of OZ277 and Piperaquine, against Different Developmental Stages of Schistosoma Mansoni. Acta Trop. 2015, 143, 36–46. [Google Scholar] [CrossRef]
  24. Sen, R.; Bandyopadhyay, S.; Dutta, A.; Mandal, G.; Ganguly, S.; Saha, P.; Chatterjee, M. Artemisinin Triggers Induction of Cell-Cycle Arrest and Apoptosis in Leishmania Donovani Promastigotes. J. Med. Microbiol. 2007, 56, 1213–1218. [Google Scholar] [CrossRef]
  25. Biamonte, M.A.; Wanner, J.; Le Roch, K.G. Recent Advances in Malaria Drug Discovery. Bioorg. Med. Chem. Lett. 2013, 23, 2829–2843. [Google Scholar] [CrossRef]
  26. Burrows, J.N.; Chibale, K.; Wells, T.N. The State of the Art in Anti-Malarial Drug Discovery and Development. Curr. Top. Med. Chem. 2011, 11, 1226–1254. [Google Scholar] [CrossRef]
  27. Lowe, M.A.; Cardenas, A.; Valentin, J.-P.; Zhu, Z.; Abendroth, J.; Castro, J.L.; Class, R.; Delaunois, A.; Fleurance, R.; Gerets, H.; et al. Discovery and Characterization of Potent, Efficacious, Orally Available Antimalarial Plasmepsin X Inhibitors and Preclinical Safety Assessment of UCB7362. J. Med. Chem. 2022, 65, 14121–14143. [Google Scholar] [CrossRef]
  28. Baragaña, B.; Norcross, N.R.; Wilson, C.; Porzelle, A.; Hallyburton, I.; Grimaldi, R.; Osuna-Cabello, M.; Norval, S.; Riley, J.; Stojanovski, L.; et al. Discovery of a Quinoline-4-Carboxamide Derivative with a Novel Mechanism of Action, Multistage Antimalarial Activity, and Potent in Vivo Efficacy. J. Med. Chem. 2016, 59, 9672–9685. [Google Scholar] [CrossRef]
  29. Greenwood, B. Malaria—Obstacles and Opportunities. Parasitol. Today 1992, 8, 391. [Google Scholar] [CrossRef]
  30. De Niz, M.; Heussler, V.T. Rodent Malaria Models: Insights into Human Disease and Parasite Biology. Curr. Opin. Microbiol. 2018, 46, 93–101. [Google Scholar] [CrossRef]
  31. Zuberi, A.; Lutz, C. Mouse Models for Drug Discovery. Can New Tools and Technology Improve Translational Power? ILAR J. 2016, 57, 178–185. [Google Scholar] [CrossRef]
  32. Olatunde, A.C.; Cornwall, D.H.; Roedel, M.; Lamb, T.J. Mouse Models for Unravelling Immunology of Blood Stage Malaria. Vaccines 2022, 10, 1525. [Google Scholar] [CrossRef]
  33. Stephens, R.; Culleton, R.L.; Lamb, T.J. The Contribution of Plasmodium chabaudi to Our Understanding of Malaria. Trends Parasitol. 2012, 28, 73–82. [Google Scholar] [CrossRef]
  34. Flannery, E.L.; Foquet, L.; Chuenchob, V.; Fishbaugher, M.; Billman, Z.; Navarro, M.J.; Betz, W.; Olsen, T.M.; Lee, J.; Camargo, N.; et al. Assessing Drug Efficacy against Plasmodium falciparum Liver Stages in Vivo. JCI Insight 2018, 3, e92587. [Google Scholar] [CrossRef]
  35. Lin, J.; Zeng, S.; Chen, Q.; Liu, G.; Pan, S.; Liu, X. Identification of Disease-Related Genes in Plasmodium berghei by Network Module Analysis. BMC Microbiol. 2023, 23, 264. [Google Scholar] [CrossRef]
  36. Simwela, N.V.; Stokes, B.H.; Aghabi, D.; Bogyo, M.; Fidock, D.A.; Waters, A.P. Plasmodium berghei K13 Mutations Mediate In Vivo Artemisinin Resistance That Is Reversed by Proteasome Inhibition. MBio 2020, 11. [Google Scholar] [CrossRef]
  37. Gifford, A.J. A Primer for Research Scientists on Assessing Mouse Gross and Histopathology Images in the Biomedical Literature. Curr. Protoc. 2023, 3, e891. [Google Scholar] [CrossRef]
  38. Singh, V.K.; Seed, T.M. How Necessary Are Animal Models for Modern Drug Discovery? Expert Opin. Drug Discov. 2021, 16, 1391–1397. [Google Scholar] [CrossRef]
  39. Shibui, A.; Hozumi, N.; Shiraishi, C.; Sato, Y.; Iida, H.; Sugano, S.; Watanabe, J. CD4+ T Cell Response in Early Erythrocytic Stage Malaria: Plasmodium berghei Infection in BALB/c and C57BL/6 Mice. Parasitol. Res. 2009, 105, 281. [Google Scholar] [CrossRef]
  40. Corral-Ruiz, G.M.; Pérez-Vega, M.J.; Galán-Salinas, A.; Mancilla-Herrera, I.; Barrios-Payán, J.; Fabila-Castillo, L.; Hernández-Pando, R.; Sánchez-Torres, L.E. Thymic Atrophy Induced by Plasmodium berghei ANKA and Plasmodium yoelii 17XL Infection. Immunol. Lett. 2023, 264, 4–16. [Google Scholar] [CrossRef]
  41. Imai, T.; Ngo-Thanh, H.; Suzue, K.; Shimo, A.; Nakamura, A.; Horiuchi, Y.; Hisaeda, H.; Murakami, T. Live Vaccination with Blood-Stage Plasmodium yoelii 17XNL Prevents the Development of Experimental Cerebral Malaria. Vaccines 2022, 10, 762. [Google Scholar] [CrossRef]
  42. Siddiqui, A.J.; Bhardwaj, J.; Puri, S.K. mRNA Expression of Cytokines and Its Impact on Outcomes after Infection with Lethal and Nonlethal Plasmodium Vinckei Parasites. Parasitol. Res. 2012, 110, 1517–1524. [Google Scholar] [CrossRef]
  43. Sedegah, M.; Finkelman, F.; Hoffman, S.L. Interleukin 12 Induction of Interferon Gamma-Dependent Protection against Malaria. Proc. Natl. Acad. Sci. USA 1994, 91, 10700–10702. [Google Scholar] [CrossRef]
  44. Conteh, S.; Kolasny, J.; Robbins, Y.L.; Pyana, P.; Büscher, P.; Musgrove, J.; Butler, B.; Lambert, L.; Gorres, J.P.; Duffy, P.E. Dynamics and Outcomes of Plasmodium Infections in Grammomys Surdaster (Grammomys Dolichurus) Thicket Rats versus Inbred Mice. Am. J. Trop. Med. Hyg. 2020, 103, 1893–1901. [Google Scholar] [CrossRef]
  45. Peter, A.E.; Sudhakar, P.; Sandeep, B.V.; Rao, B.G.; Kalpana, V.L. Murine Models for Development of Anti-Infective Therapeutics. In Model Organisms for Microbial Pathogenesis, Biofilm Formation and Antimicrobial Drug Discovery; Springer: Singapore, 2020; pp. 611–655. [Google Scholar]
  46. Olanlokun, J.O.; Abiodun, W.O.; Ebenezer, O.; Koorbanally, N.A.; Olorunsogo, O.O. Curcumin Modulates Multiple Cell Death, Matrix Metalloproteinase Activation and Cardiac Protein Release in Susceptible and Resistant Plasmodium Berghei-Infected Mice. Biomed. Pharmacother. 2022, 146, 112454. [Google Scholar] [CrossRef] [PubMed]
  47. Comino Garcia-Munoz, A.; Varlet, I.; Grau, G.E.; Perles-Barbacaru, T.-A.; Viola, A. Contribution of Magnetic Resonance Imaging Studies to the Understanding of Cerebral Malaria Pathogenesis. Pathogens 2024, 13, 1042. [Google Scholar] [CrossRef]
  48. Sriboonvorakul, N.; Chotivanich, K.; Silachamroon, U.; Phumratanaprapin, W.; Adams, J.H.; Dondorp, A.M.; Leopold, S.J. Intestinal Injury and the Gut Microbiota in Patients with Plasmodium falciparum Malaria. PLoS Pathog. 2023, 19, e1011661. [Google Scholar] [CrossRef] [PubMed]
  49. Kamaraj, C.; Ragavendran, C.; Kumar, R.C.S.; Ali, A.; Khan, S.U.; Mashwani, Z.U.-R.; Luna-Arias, J.P.; Pedroza, J.P.R. Antiparasitic Potential of Asteraceae Plants: A Comprehensive Review on Therapeutic and Mechanistic Aspects for Biocompatible Drug Discovery. Phytomed. Plus 2022, 2, 100377. [Google Scholar] [CrossRef]
  50. Nevagi, R.J.; Good, M.F.; Stanisic, D.I. Plasmodium Infection and Drug Cure for Malaria Vaccine Development. Expert Rev. Vaccines 2021, 20, 163–183. [Google Scholar] [CrossRef]
  51. Nakamura, H. BALB/c Mouse. In Brenner’s Encyclopedia of Genetics; Elsevier: Amsterdam, The Netherlands, 2013; pp. 290–292. [Google Scholar]
  52. Barr, J.T.; Tran, T.B.; Rock, B.M.; Wahlstrom, J.L.; Dahal, U.P. Strain-Dependent Variability of Early Discovery Small Molecule Pharmacokinetics in Mice: Does Strain Matter? Drug Metab. Dispos. 2020, 48, 613–621. [Google Scholar] [CrossRef]
  53. Cimperman, C.K.; Pena, M.; Gokcek, S.M.; Theall, B.P.; Patel, M.V.; Sharma, A.; Qi, C.; Sturdevant, D.; Miller, L.H.; Collins, P.L.; et al. Cerebral Malaria Is Regulated by Host-Mediated Changes in Plasmodium Gene Expression. MBio 2023, 14, e0339122. [Google Scholar] [CrossRef]
  54. Muqbil, I.; Philip, P.A.; Mohammad, R.M. A Guide to Tumor Assessment Methodologies in Cancer Drug Discovery. In Animal Models in Cancer Drug Discovery; Elsevier: Amsterdam, The Netherlands, 2019; pp. 233–248. [Google Scholar]
  55. Aubouy, A.; Camara, A.; Haddad, M. Medicinal Plants from West Africa Used as Antimalarial Agents: An Overview. In Medicinal Plants as Anti-Infectives; Elsevier: Amsterdam, The Netherlands, 2022; pp. 267–306. [Google Scholar]
  56. Hernandez-Valladares, M.; Rihet, P.; Iraqi, F.A. Host Susceptibility to Malaria in Human and Mice: Compatible Approaches to Identify Potential Resistant Genes. Physiol. Genomics 2014, 46, 1–16. [Google Scholar] [CrossRef]
  57. Patel, S.N.; Berghout, J.; Lovegrove, F.E.; Ayi, K.; Conroy, A.; Serghides, L.; Min-oo, G.; Gowda, D.C.; Sarma, J.V.; Rittirsch, D.; et al. C5 Deficiency and C5a or C5aR Blockade Protects against Cerebral Malaria. J. Exp. Med. 2008, 205, 1133–1143. [Google Scholar] [CrossRef]
  58. Wong, A.A.; Brown, R.E. Visual Detection, Pattern Discrimination and Visual Acuity in 14 Strains of Mice. Genes Brain Behav. 2006, 5, 389–403. [Google Scholar] [CrossRef]
  59. Huang, H.M.; McMorran, B.J.; Foote, S.J.; Burgio, G. Host Genetics in Malaria: Lessons from Mouse Studies. Mamm. Genome 2018, 29, 507–522. [Google Scholar] [CrossRef]
  60. Zhang, Y.; Richter, N.; König, C.; Kremer, A.E.; Zimmermann, K. Generalized Resistance to Pruritogen-Induced Scratching in the C3H/HeJ Strain. Front. Mol. Neurosci. 2022, 15, 934564. [Google Scholar] [CrossRef]
  61. Vydyam, P.; Chand, M.; Gihaz, S.; Renard, I.; Heffernan, G.D.; Jacobus, L.R.; Jacobus, D.P.; Saionz, K.W.; Shah, R.; Shieh, H.-M.; et al. In Vitro Efficacy of Next-Generation Dihydrotriazines and Biguanides against Babesiosis and Malaria Parasites. Antimicrob. Agents Chemother. 2024, 68, e0042324. [Google Scholar] [CrossRef]
  62. Djokic, V.; Akoolo, L.; Parveen, N. Babesia Microti Infection Changes Host Spleen Architecture and Is Cleared by a Th1 Immune Response. Front. Microbiol. 2018, 9, 85. [Google Scholar] [CrossRef]
  63. Lohse, A.W.; Büschenfelde, K.-H.M. zum Experimental Hepatitis. In Autoimmune Disease Models; Elsevier: Amsterdam, The Netherlands, 1994; pp. 191–199. [Google Scholar]
  64. Su, X.; Wu, J.; Xu, F.; Pattaradilokrat, S. Genetic Mapping of Determinants in Drug Resistance, Virulence, Disease Susceptibility, and Interaction of Host-Rodent Malaria Parasites. Parasitol. Int. 2022, 91, 102637. [Google Scholar] [CrossRef]
  65. Charles River CBA Mice. Available online: https://www.criver.com/products-services/find-model/cba-mouse?region=3616 (accessed on 11 February 2025).
  66. Schnider, C.B.; Yang, H.; Starrs, L.; Ehmann, A.; Rahimi, F.; Di Pierro, E.; Graziadei, G.; Matthews, K.; De Koning-Ward, T.; Bauer, D.C.; et al. Host Porphobilinogen Deaminase Deficiency Confers Malaria Resistance in Plasmodium chabaudi but Not in Plasmodium berghei or Plasmodium falciparum During Intraerythrocytic Growth. Front. Cell. Infect. Microbiol. 2020, 10, 464. [Google Scholar] [CrossRef]
  67. Sunita, K.; Rajyalakshmi, M.; Kalyan Kumar, K.; Sowjanya, M.; Satish, P.V.V.; Madhu Prasad, D. Human Malaria in C57BL/6J Mice: An in Vivo Model for Chemotherapy Studies. Indian J. Exp. Biol. 2014, 52, 67–72. [Google Scholar]
  68. Chen, Y.; Zhu, F.; Hammill, J.; Holbrook, G.; Yang, L.; Freeman, B.; White, K.L.; Shackleford, D.M.; O’Loughlin, K.G.; Charman, S.A.; et al. Selecting an Anti-Malarial Clinical Candidate from Two Potent Dihydroisoquinolones. Malar. J. 2021, 20, 107. [Google Scholar] [CrossRef] [PubMed]
  69. An, J.; Woodward, J.J.; Lai, W.; Minie, M.; Sun, X.; Tanaka, L.; Snyder, J.M.; Sasaki, T.; Elkon, K.B. Inhibition of Cyclic GMP-AMP Synthase Using a Novel Antimalarial Drug Derivative in Trex1-Deficient Mice. Arthritis Rheumatol. 2018, 70, 1807–1819. [Google Scholar] [CrossRef]
  70. Gujjari, L.; Kalani, H.; Pindiprolu, S.K.; Arakareddy, B.P.; Yadagiri, G. Current Challenges and Nanotechnology-Based Pharmaceutical Strategies for the Treatment and Control of Malaria. Parasite Epidemiol. Control 2022, 17, e00244. [Google Scholar] [CrossRef]
  71. Simwela, N.V.; Waters, A.P. Current Status of Experimental Models for the Study of Malaria. Parasitology 2022, 149, 729–750. [Google Scholar] [CrossRef]
  72. Acosta, M.M.; Bram, J.T.; Sim, D.; Read, A.F. Effect of Drug Dose and Timing of Treatment on the Emergence of Drug Resistance in Vivo in a Malaria Model. Evol. Med. Public Health 2020, 2020, 196–210. [Google Scholar] [CrossRef]
  73. Langhorne, J.; Buffet, P.; Galinski, M.; Good, M.; Harty, J.; Leroy, D.; Mota, M.M.; Pasini, E.; Renia, L.; Riley, E.; et al. The Relevance of Non-Human Primate and Rodent Malaria Models for Humans. Malar. J. 2011, 10, 23. [Google Scholar] [CrossRef]
  74. Chunduri, A.; Watson, P.M.; Ashbrook, D.G. New Insights on Gene by Environmental Effects of Drugs of Abuse in Animal Models Using GeneNetwork. Genes 2022, 13, 614. [Google Scholar] [CrossRef]
  75. Parks, C.; Giorgianni, F.; Jones, B.C.; Beranova-Giorgianni, S.; Moore II, B.M.; Mulligan, M.K. Comparison and Functional Genetic Analysis of Striatal Protein Expression Among Diverse Inbred Mouse Strains. Front. Mol. Neurosci. 2019, 12, 128. [Google Scholar] [CrossRef]
  76. Novita, R.; Suprayogi, A.; Agusta, A.; Nugraha, A.; Nozaki, T.; Agustini, K.; Darusman, H. Antimalarial Activity of Borrelidin and Fumagilin in Plasmodium Berghei-Infected Mice. Open Vet. J. 2024, 14, 2007. [Google Scholar] [CrossRef]
  77. Hermanto, F.; Sutjiatmo, A.B.; Subarnas, A.; Haq, F.A.; Berbudi, A. The Combination of Apigenin and Ursolic Acid Reduces the Severity of Cerebral Malaria in Plasmodium berghei ANKA-Infected Swiss Webster Mice. J. Appl. Pharm. Sci. 2023, 14, 141–147. [Google Scholar] [CrossRef]
  78. Annang, F.; Pérez-Moreno, G.; Díaz, C.; González-Menéndez, V.; de Pedro Montejo, N.; del Palacio, J.P.; Sánchez, P.; Tanghe, S.; Rodriguez, A.; Pérez-Victoria, I.; et al. Preclinical Evaluation of Strasseriolides A–D, Potent Antiplasmodial Macrolides Isolated from Strasseria Geniculata CF-247,251. Malar. J. 2021, 20, 457. [Google Scholar] [CrossRef]
  79. Aly, N.S.M.; Matsumori, H.; Dinh, T.Q.; Sato, A.; Miyoshi, S.-I.; Chang, K.-S.; Yu, H.S.; Kobayashi, F.; Kim, H.-S. Antimalarial Effect of Synthetic Endoperoxide on Synchronized Plasmodium chabaudi Infected Mice. Parasites, Hosts Dis. 2023, 61, 33–41. [Google Scholar] [CrossRef]
  80. Ounjaijean, S.; Romyasamit, C.; Somsak, V. Evaluation of Antimalarial Potential of Aqueous Crude Gymnema Inodorum Leaf Extract against Plasmodium berghei Infection in Mice. Evidence-Based Complement. Altern. Med. 2021, 2021, 9932891. [Google Scholar] [CrossRef]
  81. Ounjaijean, S.; Somsak, V. Exploring the Antimalarial Potential of Gnetum Gnemon Leaf Extract Against Plasmodium berghei in Mice. J. Trop. Med. 2024, 2024, 3471083. [Google Scholar] [CrossRef]
  82. Chaniad, P.; Techarang, T.; Phuwajaroanpong, A.; Na-ek, P.; Viriyavejakul, P.; Punsawad, C. In Vivo Antimalarial Activity and Toxicity Study of Extracts of Tagetes erecta L. and Synedrella nodiflora (L.) Gaertn. from the Asteraceae Family. Evidence-Based Complement. Altern. Med. 2021, 2021, 1270902. [Google Scholar] [CrossRef]
  83. Klope, M.T.; Tapia Cardona, J.A.; Chen, J.; Gonciarz, R.L.; Cheng, K.; Jaishankar, P.; Kim, J.; Legac, J.; Rosenthal, P.J.; Renslo, A.R. Synthesis and In Vivo Profiling of Desymmetrized Antimalarial Trioxolanes with Diverse Carbamate Side Chains. ACS Med. Chem. Lett. 2024, 15, 1764–1770. [Google Scholar] [CrossRef]
  84. Burgert, L.; Rottmann, M.; Wittlin, S.; Gobeau, N.; Krause, A.; Dingemanse, J.; Möhrle, J.J.; Penny, M.A. Ensemble Modeling Highlights Importance of Understanding Parasite-Host Behavior in Preclinical Antimalarial Drug Development. Sci. Rep. 2020, 10, 4410. [Google Scholar] [CrossRef]
  85. Burgert, L.; Zaloumis, S.; Dini, S.; Marquart, L.; Cao, P.; Cherkaoui, M.; Gobeau, N.; McCarthy, J.; Simpson, J.A.; Möhrle, J.J.; et al. Parasite-Host Dynamics throughout Antimalarial Drug Development Stages Complicate the Translation of Parasite Clearance. Antimicrob. Agents Chemother. 2021, 65. [Google Scholar] [CrossRef]
  86. Khandelwal, A.; Arez, F.; Alves, P.M.; Badolo, L.; Brito, C.; Fischli, C.; Fontinha, D.; Oeuvray, C.; Prudêncio, M.; Rottmann, M.; et al. Translation of Liver Stage Activity of M5717, a Plasmodium Elongation Factor 2 Inhibitor: From Bench to Bedside. Malar. J. 2022, 21, 151. [Google Scholar] [CrossRef]
  87. Moreno, A.; Ferrer, E.; Arahuetes, S.; Eguiluz, C.; Van Rooijen, N.; Benito, A. The Course of Infections and Pathology in Immunomodulated NOD/LtSz-SCID Mice Inoculated with Plasmodium falciparum Laboratory Lines and Clinical Isolates. Int. J. Parasitol. 2006, 36, 361–369. [Google Scholar] [CrossRef]
  88. Tejada, M.A.; Antunez, C.; Nunez-Badinez, P.; De Leo, B.; Saunders, P.T.; Vincent, K.; Cano, A.; Nagel, J.; Gomez, R. Rodent Animal Models of Endometriosis-Associated Pain: Unmet Needs and Resources Available for Improving Translational Research in Endometriosis. Int. J. Mol. Sci. 2023, 24, 2422. [Google Scholar] [CrossRef]
  89. Salazar-Castañón, V.H.; Juárez-Avelar, I.; Legorreta-Herrera, M.; Rodriguez-Sosa, M. Macrophage Migration Inhibitory Factor Contributes to Immunopathogenesis during Plasmodium yoelii 17XL Infection. Front. Cell. Infect. Microbiol. 2022, 12, 968422. [Google Scholar] [CrossRef]
  90. Rayner, C.R.; Smith, P.F.; Andes, D.; Andrews, K.; Derendorf, H.; Friberg, L.E.; Hanna, D.; Lepak, A.; Mills, E.; Polasek, T.M.; et al. Model-Informed Drug Development for Anti-Infectives: State of the Art and Future. Clin. Pharmacol. Ther. 2021, 109, 867–891. [Google Scholar] [CrossRef]
  91. Aparici Herraiz, I.; Caires, H.R.; Castillo-Fernández, Ó.; Sima, N.; Méndez-Mora, L.; Risueño, R.M.; Sattabongkot, J.; Roobsoong, W.; Hernández-Machado, A.; Fernandez-Becerra, C.; et al. Advancing Key Gaps in the Knowledge of Plasmodium vivax Cryptic Infections Using Humanized Mouse Models and Organs-on-Chips. Front. Cell. Infect. Microbiol. 2022, 12, 920204. [Google Scholar] [CrossRef]
  92. O’Neill, P.M.; Amewu, R.K.; Charman, S.A.; Sabbani, S.; Gnädig, N.F.; Straimer, J.; Fidock, D.A.; Shore, E.R.; Roberts, N.L.; Wong, M.H.-L.; et al. A Tetraoxane-Based Antimalarial Drug Candidate That Overcomes PfK13-C580Y Dependent Artemisinin Resistance. Nat. Commun. 2017, 8, 15159. [Google Scholar] [CrossRef]
  93. Goswami, D.; Kumar, S.; Betz, W.; Armstrong, J.M.; Haile, M.T.; Camargo, N.; Parthiban, C.; Seilie, A.M.; Murphy, S.C.; Vaughan, A.M.; et al. A Plasmodium falciparum ATP-Binding Cassette Transporter Is Essential for Liver Stage Entry into Schizogony. iScience 2022, 25, 104224. [Google Scholar] [CrossRef]
  94. Oblak, A.L.; Lin, P.B.; Kotredes, K.P.; Pandey, R.S.; Garceau, D.; Williams, H.M.; Uyar, A.; O’Rourke, R.; O’Rourke, S.; Ingraham, C.; et al. Comprehensive Evaluation of the 5XFAD Mouse Model for Preclinical Testing Applications: A MODEL-AD Study. Front. Aging Neurosci. 2021, 13, 713726. [Google Scholar] [CrossRef]
  95. Kioko, M.; Mwangi, S.; Njunge, J.M.; Berkley, J.A.; Bejon, P.; Abdi, A.I. Linking Cerebral Malaria Pathogenesis to APOE-Mediated Amyloidosis: Observations and Hypothesis. Mol. Neurobiol. 2024, 62, 1720–1725. [Google Scholar] [CrossRef]
  96. Kisler, K.; Sagare, A.P.; Lazic, D.; Bazzi, S.; Lawson, E.; Hsu, C.-J.; Wang, Y.; Ramanathan, A.; Nelson, A.R.; Zhao, Z.; et al. Anti-Malaria Drug Artesunate Prevents Development of Amyloid-β Pathology in Mice by Upregulating PICALM at the Blood-Brain Barrier. Mol. Neurodegener. 2023, 18, 7. [Google Scholar] [CrossRef]
  97. McCarthy, J.S.; Marquart, L.; Sekuloski, S.; Trenholme, K.; Elliott, S.; Griffin, P.; Rockett, R.; O’Rourke, P.; Sloots, T.; Angulo-Barturen, I.; et al. Linking Murine and Human Plasmodium falciparum Challenge Models in a Translational Path for Antimalarial Drug Development. Antimicrob. Agents Chemother. 2016, 60, 3669–3675. [Google Scholar] [CrossRef]
  98. Bryant, C.D.; Ferris, M.T.; De Villena, F.P.M.; Damaj, M.I.; Kumar, V.; Mulligan, M.K. Reduced Complexity Cross Design for Behavioral Genetics. In Molecular-Genetic and Statistical Techniques for Behavioral and Neural Research; Elsevier: Amsterdam, The Netherlands, 2018; pp. 165–190. [Google Scholar]
  99. Rocha e Silva, L.F.; Nogueira, K.L.; Pinto, A.C.d.S.; Katzin, A.M.; Sussmann, R.A.C.; Muniz, M.P.; Neto, V.F.d.A.; Chaves, F.C.M.; Coutinho, J.P.; Lima, E.S.; et al. In Vivo Antimalarial Activity and Mechanisms of Action of 4-Nerolidylcatechol Derivatives. Antimicrob. Agents Chemother. 2015, 59, 3271–3280. [Google Scholar] [CrossRef]
  100. Neto, Z.; Machado, M.; Lindeza, A.; do Rosário, V.; Gazarini, M.L.; Lopes, D. Treatment of Plasmodium chabaudi Parasites with Curcumin in Combination with Antimalarial Drugs: Drug Interactions and Implications on the Ubiquitin/Proteasome System. J. Parasitol. Res. 2013, 2013, 429736. [Google Scholar] [CrossRef]
  101. Saroa, R.; Kaushik, D.; Rakha, A.; Bagai, U.; Kaur, S.; Salunke, D.B. Pure TLR 7 Agonistic BBIQ Is a Potential Adjuvant Against Plasmodium berghei ANKA Challenge In Vivo. In Drug Development for Malaria; Wiley: Hoboken, NJ, USA, 2022; pp. 353–366. [Google Scholar]
  102. PERCY, D.H. Sphingomyelin Lipidosis (Niemann-Pick Disease). In Spontaneous Animal Models of Human Disease; Elsevier: Amsterdam, The Netherlands, 1979; pp. 132–133. [Google Scholar]
  103. Davis, M.J.; Martin, R.E.; Pinheiro, G.M.; Hoke, E.S.; Moyer, S.; Ueno, K.; Rodriguez-Gil, J.L.; Mallett, M.A.; Khillan, J.S.; Pavan, W.J.; et al. Inbred SJL Mice Recapitulate Human Resistance to Cryptococcus Infection Due to Differential Immune Activation. MBio 2023, 14, e0212323. [Google Scholar] [CrossRef]
  104. Sonoiki, E.; Ng, C.L.; Lee, M.C.S.; Guo, D.; Zhang, Y.-K.; Zhou, Y.; Alley, M.R.K.; Ahyong, V.; Sanz, L.M.; Lafuente-Monasterio, M.J.; et al. A Potent Antimalarial Benzoxaborole Targets a Plasmodium falciparum Cleavage and Polyadenylation Specificity Factor Homologue. Nat. Commun. 2017, 8, 14574. [Google Scholar] [CrossRef]
  105. Rios, K.T.; Dickson, T.M.; Lindner, S.E. Standard Selection Treatments with Sulfadiazine Limit Plasmodium yoelii Host-to-Vector Transmission. mSphere 2022, 7, e0010622. [Google Scholar] [CrossRef]
  106. Draper, M.P.; Bhatia, B.; Assefa, H.; Honeyman, L.; Garrity-Ryan, L.K.; Verma, A.K.; Gut, J.; Larson, K.; Donatelli, J.; Macone, A.; et al. In Vitro and In Vivo Antimalarial Efficacies of Optimized Tetracyclines. Antimicrob. Agents Chemother. 2013, 57, 3131–3136. [Google Scholar] [CrossRef]
  107. Jezewski, A.J.; Lin, Y.-H.; Reisz, J.A.; Culp-Hill, R.; Barekatain, Y.; Yan, V.C.; D’Alessandro, A.; Muller, F.L.; Odom John, A.R. Targeting Host Glycolysis as a Strategy for Antimalarial Development. Front. Cell. Infect. Microbiol. 2021, 11, 730413. [Google Scholar] [CrossRef]
  108. Marrelli, M.T.; Wang, Z.; Huang, J.; Brotto, M. The Skeletal Muscles of Mice Infected with Plasmodium berghei and Plasmodium chabaudi Reveal a Crosstalk between Lipid Mediators and Gene Expression. Malar. J. 2020, 19, 254. [Google Scholar] [CrossRef]
  109. Xie, Y.; Zhang, Y.; Lin, F.; Chen, X.; Xing, J. The Effect of Malaria-Induced Alteration of Metabolism on Piperaquine Disposition in Plasmodium yoelii Infected Mice and Predicted in Malaria Patients. Int. J. Antimicrob. Agents 2024, 64, 107209. [Google Scholar] [CrossRef]
  110. Ha, Y.R.; Kang, Y.-J.; Lee, S.J. In Vivo Study on Splenomegaly Inhibition by Genistein in Plasmodium berghei-Infected Mice. Parasitol. Int. 2015, 64, 369–376. [Google Scholar] [CrossRef]
  111. Ramaprasad, A.; Klaus, S.; Douvropoulou, O.; Culleton, R.; Pain, A. Plasmodium vinckei Genomes Provide Insights into the Pan-Genome and Evolution of Rodent Malaria Parasites. BMC Biol. 2021, 19, 69. [Google Scholar] [CrossRef]
  112. Chaniad, P.; Techarang, T.; Phuwajaroanpong, A.; Plirat, W.; Viriyavejakul, P.; Septama, A.W.; Punsawad, C. Antimalarial Efficacy and Toxicological Assessment of Medicinal Plant Ingredients of Prabchompoothaweep Remedy as a Candidate for Antimalarial Drug Development. BMC Complement. Med. Ther. 2023, 23, 12. [Google Scholar] [CrossRef]
  113. Hong, H.; Moon, K.; Trinh, T.-T.T.; Eom, T.-H.; Park, H.; Kim, H.S.; Yeo, S.-J. Evaluation of the Antimalarial Activity of SAM13-2HCl with Morpholine Amide (SKM13 Derivative) against Antimalarial Drug-Resistant Plasmodium falciparum and Plasmodium berghei Infected ICR Mice. Parasites Hosts Dis. 2024, 62, 42–52. [Google Scholar] [CrossRef]
  114. Degotte, G.; Pendeville, H.; Di Chio, C.; Ettari, R.; Pirotte, B.; Frédérich, M.; Francotte, P. Dimeric Polyphenols to Pave the Way for New Antimalarial Drugs. RSC Med. Chem. 2023, 14, 715–733. [Google Scholar] [CrossRef]
  115. Yeates, C.L.; Batchelor, J.F.; Capon, E.C.; Cheesman, N.J.; Fry, M.; Hudson, A.T.; Pudney, M.; Trimming, H.; Woolven, J.; Bueno, J.M.; et al. Synthesis and Structure–Activity Relationships of 4-Pyridones as Potential Antimalarials. J. Med. Chem. 2008, 51, 2845–2852. [Google Scholar] [CrossRef]
  116. Chughlay, M.F.; El Gaaloul, M.; Donini, C.; Campo, B.; Berghmans, P.-J.; Lucardie, A.; Marx, M.W.; Cherkaoui-Rbati, M.H.; Langdon, G.; Angulo-Barturen, I.; et al. Chemoprotective Antimalarial Activity of P218 against Plasmodium falciparum: A Randomized, Placebo-Controlled Volunteer Infection Study. Am. J. Trop. Med. Hyg. 2021, 104, 1348–1358. [Google Scholar] [CrossRef]
  117. Basilico, N.; Parapini, S.; D’Alessandro, S.; Misiano, P.; Romeo, S.; Dondio, G.; Yardley, V.; Vivas, L.; Nasser, S.; Rénia, L.; et al. Favorable Preclinical Pharmacological Profile of a Novel Antimalarial Pyrrolizidinylmethyl Derivative of 4-Amino-7-Chloroquinoline with Potent In Vitro and In Vivo Activities. Biomolecules 2023, 13, 836. [Google Scholar] [CrossRef]
  118. Dobrescu, I.; de Camargo, T.M.; Gimenez, A.M.; Murillo, O.; Amorim, K.N.d.S.; Marinho, C.R.F.; Soares, I.S.; Boscardin, S.B.; Bargieri, D.Y. Protective Immunity in Mice Immunized with P. vivax MSP119-Based Formulations and Challenged with P. berghei Expressing PvMSP119. Front. Immunol. 2020, 11, 28. [Google Scholar] [CrossRef]
  119. Andrews, K.A.; Wesche, D.; McCarthy, J.; Möhrle, J.J.; Tarning, J.; Phillips, L.; Kern, S.; Grasela, T. Model-Informed Drug Development for Malaria Therapeutics. Annu. Rev. Pharmacol. Toxicol. 2018, 58, 567–582. [Google Scholar] [CrossRef]
  120. Yang, T.; Ottilie, S.; Istvan, E.S.; Godinez-Macias, K.P.; Lukens, A.K.; Baragaña, B.; Campo, B.; Walpole, C.; Niles, J.C.; Chibale, K.; et al. MalDA, Accelerating Malaria Drug Discovery. Trends Parasitol. 2021, 37, 493–507. [Google Scholar] [CrossRef]
  121. Brancucci, N.M.B.; Gumpp, C.; van Gemert, G.-J.; Yu, X.; Passecker, A.; Nardella, F.; Thommen, B.T.; Chambon, M.; Turcatti, G.; Halby, L.; et al. An All-in-One Pipeline for the in Vitro Discovery and in Vivo Testing of Plasmodium falciparum Malaria Transmission Blocking Drugs. bioRxiv 2024. [Google Scholar] [CrossRef]
  122. Baragaña, B.; Forte, B.; Choi, R.; Nakazawa Hewitt, S.; Bueren-Calabuig, J.A.; Pisco, J.P.; Peet, C.; Dranow, D.M.; Robinson, D.A.; Jansen, C.; et al. Lysyl-TRNA Synthetase as a Drug Target in Malaria and Cryptosporidiosis. Proc. Natl. Acad. Sci. USA 2019, 116, 7015–7020. [Google Scholar] [CrossRef]
  123. Tyagi, R.K. Plasmodium falciparum-Infected Humanized Mice: A Viable Preclinical Tool. Immunotherapy 2021, 13, 1345–1353. [Google Scholar] [CrossRef]
  124. Okombo, J.; Kanai, M.; Deni, I.; Fidock, D.A. Genomic and Genetic Approaches to Studying Antimalarial Drug Resistance and Plasmodium Biology. Trends Parasitol. 2021, 37, 476–492. [Google Scholar] [CrossRef]
  125. Hewitt, P.; Hartmann, A.; Tornesi, B.; Ferry-Martin, S.; Valentin, J.-P.; Desert, P.; Gresham, S.; Demarta-Gatsi, C.; Venishetty, V.K.; Kolly, C. Importance of Tailored Non-Clinical Safety Testing of Novel Antimalarial Drugs: Industry Best-Practice. Regul. Toxicol. Pharmacol. 2024, 154, 105736. [Google Scholar] [CrossRef]
  126. Brehm, M.A.; Shultz, L.D.; Luban, J.; Greiner, D.L. Overcoming Current Limitations in Humanized Mouse Research. J. Infect. Dis. 2013, 208 (Suppl. 2), S125–S130. [Google Scholar] [CrossRef]
  127. Chen, B.; Liu, H.; Liu, Z.; Yang, F. Benefits and Limitations of Humanized Mouse Models for Human Red Blood Cell-Related Disease Research. Front. Hematol. 2023, 1, 1062705. [Google Scholar] [CrossRef]
  128. Okombo, J.; Chibale, K. Recent Updates in the Discovery and Development of Novel Antimalarial Drug Candidates. Medchemcomm 2018, 9, 437–453. [Google Scholar] [CrossRef]
  129. Yeung, B.K. KAE609 (Cipargamin): Discovery of Spiroindolone Antimalarials. In Comprehensive Medicinal Chemistry III; Elsevier: Amsterdam, The Netherlands, 2017; pp. 529–543. [Google Scholar]
  130. Mak, K.-K.; Epemolu, O.; Pichika, M.R. The Role of DMPK Science in Improving Pharmaceutical Research and Development Efficiency. Drug Discov. Today 2022, 27, 705–729. [Google Scholar] [CrossRef]
  131. Musther, H.; Olivares-Morales, A.; Hatley, O.J.D.; Liu, B.; Rostami Hodjegan, A. Animal versus Human Oral Drug Bioavailability: Do They Correlate? Eur. J. Pharm. Sci. 2014, 57, 280–291. [Google Scholar] [CrossRef]
  132. Fu, C.; Shi, H.; Chen, H.; Zhang, K.; Wang, M.; Qiu, F. Oral Bioavailability Comparison of Artemisinin, Deoxyartemisinin, and 10-Deoxoartemisinin Based on Computer Simulations and Pharmacokinetics in Rats. ACS Omega 2021, 6, 889–899. [Google Scholar] [CrossRef]
  133. Stielow, M.; Witczyńska, A.; Kubryń, N.; Fijałkowski, Ł.; Nowaczyk, J.; Nowaczyk, A. The Bioavailability of Drugs—The Current State of Knowledge. Molecules 2023, 28, 8038. [Google Scholar] [CrossRef]
  134. Fagerholm, U.; Hellberg, S.; Spjuth, O. Advances in Predictions of Oral Bioavailability of Candidate Drugs in Man with New Machine Learning Methodology. Molecules 2021, 26, 2572. [Google Scholar] [CrossRef]
  135. Bhanot, A.; Sundriyal, S. Physicochemical Profiling and Comparison of Research Antiplasmodials and Advanced Stage Antimalarials with Oral Drugs. ACS Omega 2021, 6, 6424–6437. [Google Scholar] [CrossRef]
  136. Li, P.; Peng, J.; Li, Y.; Gong, L.; Lv, Y.; Liu, H.; Zhang, T.; Yang, S.; Liu, H.; Li, J.; et al. Pharmacokinetics, Bioavailability, Excretion and Metabolism Studies of Akebia Saponin D in Rats: Causes of the Ultra-Low Oral Bioavailability and Metabolic Pathway. Front. Pharmacol. 2021, 12, 621003. [Google Scholar] [CrossRef]
  137. Ogienko, A.G.; Markov, A.V.; Sen’kova, A.V.; Logashenko, E.B.; Salomatina, O.V.; Myz, S.A.; Ogienko, A.A.; Nefedov, A.A.; Losev, E.A.; Drebushchak, T.N.; et al. Increasing Bioavailability of Very Poorly Water-Soluble Compounds. A Case Study of an Anti-Tumor Drug, Soloxolon Methyl. J. Drug Deliv. Sci. Technol. 2019, 49, 35–42. [Google Scholar] [CrossRef]
  138. Samby, K.; Willis, P.A.; Burrows, J.N.; Laleu, B.; Webborn, P.J.H. Actives from MMV Open Access Boxes? A Suggested Way Forward. PLoS Pathog. 2021, 17, e1009384. [Google Scholar] [CrossRef]
  139. WHO. Methods and Techniques for Assessing Exposure to Antimalarial Drugs in Clinical Field Studies. World Health 2011, 165, 423. [Google Scholar]
  140. Waithera, M.W.; Sifuna, M.W.; Kariuki, D.W.; Kinyua, J.K.; Kimani, F.T.; Ng’ang’a, J.K.; Takei, M. Antimalarial Activity Assay of Artesunate-3-Chloro-4(4-Chlorophenoxy) Aniline in Vitro and in Mice Models. Parasitol. Res. 2023, 122, 979–988. [Google Scholar] [CrossRef]
  141. Coelho, M.M.; Fernandes, C.; Remião, F.; Tiritan, M.E. Enantioselectivity in Drug Pharmacokinetics and Toxicity: Pharmacological Relevance and Analytical Methods. Molecules 2021, 26, 3113. [Google Scholar] [CrossRef]
  142. Smith, D.A.; Beaumont, K.; Maurer, T.S.; Di, L. Volume of Distribution in Drug Design. J. Med. Chem. 2015, 58, 5691–5698. [Google Scholar] [CrossRef]
  143. Hughes, E.A.; Zieliński, R.; Ray, A.E.; Priebe, W.; Douglass Junior, E.F. Development of a Novel Tool To Demystify Drug Distribution at Tissue-Blood Barriers. ChemBioChem 2023, 24, e202200804. [Google Scholar] [CrossRef]
  144. Alia, J.D.; Karl, S.; Kelly, T.D. Quantum Chemical Lipophilicities of Antimalarial Drugs in Relation to Terminal Half-Life. ACS Omega 2020, 5, 6500–6515. [Google Scholar] [CrossRef]
  145. Carucci, M.; Duez, J.; Tarning, J.; García-Barbazán, I.; Fricot-Monsinjon, A.; Sissoko, A.; Dumas, L.; Gamallo, P.; Beher, B.; Amireault, P.; et al. Safe Drugs with High Potential to Block Malaria Transmission Revealed by a Spleen-Mimetic Screening. Nat. Commun. 2023, 14, 1951. [Google Scholar] [CrossRef]
  146. Na-Bangchang, K.; Karbwang, J. Pharmacology of Antimalarial Drugs, Current Anti-Malarials. In Encyclopedia of Malaria; Springer: New York, NY, USA, 2019; pp. 1–82. [Google Scholar]
  147. Wesolowski, C.A.; Wesolowski, M.J.; Babyn, P.S.; Wanasundara, S.N. Time Varying Apparent Volume of Distribution and Drug Half-Lives Following Intravenous Bolus Injections. PLoS ONE 2016, 11, e0158798. [Google Scholar] [CrossRef]
  148. Yu, R.; Cao, Y. A Method to Determine Pharmacokinetic Parameters Based on Andante Constant-Rate Intravenous Infusion. Sci. Rep. 2017, 7, 13279. [Google Scholar] [CrossRef]
  149. Banda, C.G.; Tarning, J.; Barnes, K.I. Use of Population Pharmacokinetic-pharmacodynamic Modelling to Inform Antimalarial Dose Optimization in Infants. Br. J. Clin. Pharmacol. 2024. [Google Scholar] [CrossRef]
  150. Smith, D.A.; Di, L.; Kerns, E.H. The Effect of Plasma Protein Binding on in Vivo Efficacy: Misconceptions in Drug Discovery. Nat. Rev. Drug Discov. 2010, 9, 929–939. [Google Scholar] [CrossRef]
  151. Toma, C.-M.; Imre, S.; Vari, C.-E.; Muntean, D.-L.; Tero-Vescan, A. Ultrafiltration Method for Plasma Protein Binding Studies and Its Limitations. Processes 2021, 9, 382. [Google Scholar] [CrossRef]
  152. Di, L. An Update on the Importance of Plasma Protein Binding in Drug Discovery and Development. Expert Opin. Drug Discov. 2021, 16, 1453–1465. [Google Scholar] [CrossRef]
  153. Mhango, E.K.G.; Snorradottir, B.S.; Kachingwe, B.H.K.; Katundu, K.G.H.; Gizurarson, S. Estimation of Pediatric Dosage of Antimalarial Drugs, Using Pharmacokinetic and Physiological Approach. Pharmaceutics 2023, 15, 1076. [Google Scholar] [CrossRef]
  154. Charman, S.A.; Andreu, A.; Barker, H.; Blundell, S.; Campbell, A.; Campbell, M.; Chen, G.; Chiu, F.C.K.; Crighton, E.; Katneni, K.; et al. An in Vitro Toolbox to Accelerate Anti-Malarial Drug Discovery and Development. Malar. J. 2020, 19, 1. [Google Scholar] [CrossRef]
  155. Bteich, M. An Overview of Albumin and Alpha-1-Acid Glycoprotein Main Characteristics: Highlighting the Roles of Amino Acids in Binding Kinetics and Molecular Interactions. Heliyon 2019, 5, e02879. [Google Scholar] [CrossRef] [PubMed]
  156. Perić, M.; Fajdetić, A.; Rupčić, R.; Alihodžić, S.; Žiher, D.; Bukvić Krajačić, M.; Smith, K.S.; Ivezić-Schönfeld, Z.; Padovan, J.; Landek, G.; et al. Antimalarial Activity of 9a- N Substituted 15-Membered Azalides with Improved in Vitro and in Vivo Activity over Azithromycin. J. Med. Chem. 2012, 55, 1389–1401. [Google Scholar] [CrossRef]
  157. Moore, B.R.; Davis, T.M. Updated Pharmacokinetic Considerations for the Use of Antimalarial Drugs in Pregnant Women. Expert Opin. Drug Metab. Toxicol. 2020, 16, 741–758. [Google Scholar] [CrossRef]
  158. Yahya, M.H.; Babalola, S.A.; Idris, A.Y.; Hamza, A.N.; Igie, N.; Odeyemi, I.; Musa, A.M.; Olorukooba, A.B. Therapeutic Potency of Mono- and Diprenylated Acetophenones: A Case Study of In-Vivo Antimalarial Evaluation. Pharm. Front. 2023, 05, e15–e24. [Google Scholar] [CrossRef]
  159. Zhao, S.; Duan, H.; Yang, Y.; Yan, X.; Fan, K. Fenozyme Protects the Integrity of the Blood–Brain Barrier against Experimental Cerebral Malaria. Nano Lett. 2019, 19, 8887–8895. [Google Scholar] [CrossRef]
  160. Akide Ndunge, O.B.; Shikani, H.J.; Dai, M.; Freeman, B.D.; Desruisseaux, M.S. Effects of Anti-Tau Immunotherapy on Reactive Microgliosis, Cerebral Endotheliopathy, and Cognitive Function in an Experimental Model of Cerebral Malaria. J. Neurochem. 2023, 167, 441–460. [Google Scholar] [CrossRef]
  161. Ghazanfari, N.; Mueller, S.N.; Heath, W.R. Cerebral Malaria in Mouse and Man. Front. Immunol. 2018, 9, 2016. [Google Scholar] [CrossRef]
  162. Crowley, V.M.; Ayi, K.; Lu, Z.; Liby, K.T.; Sporn, M.; Kain, K.C. Synthetic Oleanane Triterpenoids Enhance Blood Brain Barrier Integrity and Improve Survival in Experimental Cerebral Malaria. Malar. J. 2017, 16, 463. [Google Scholar] [CrossRef]
  163. Das, N.; Prabhu, P. Emerging Avenues for the Management of Cerebral Malaria. J. Pharm. Pharmacol. 2022, 74, 800–811. [Google Scholar] [CrossRef]
  164. Goli, V.V.N.; Tatineni, S.; Hani, U.; Ghazwani, M.; Talath, S.; Sridhar, S.B.; Alhamhoom, Y.; Fatima, F.; Osmani, R.A.M.; Shivaswamy, U.; et al. Pharmacokinetics and Pharmacodynamics of a Nanostructured Lipid Carrier Co-Encapsulating Artemether and MiRNA for Mitigating Cerebral Malaria. Pharmaceuticals 2024, 17, 466. [Google Scholar] [CrossRef]
  165. Huang, G.; Solano, C.M.; Melendez, J.; Yu-Alfonzo, S.; Boonhok, R.; Min, H.; Miao, J.; Chakrabarti, D.; Yuan, Y. Discovery of Fast-Acting Dual-Stage Antimalarial Agents by Profiling Pyridylvinylquinoline Chemical Space via Copper Catalyzed Azide-Alkyne Cycloadditions. Eur. J. Med. Chem. 2021, 209, 112889. [Google Scholar] [CrossRef]
  166. Gajula, S.N.R.; Nadimpalli, N.; Sonti, R. Drug Metabolic Stability in Early Drug Discovery to Develop Potential Lead Compounds. Drug Metab. Rev. 2021, 53, 459–477. [Google Scholar] [CrossRef]
  167. Siramshetty, V.B.; Shah, P.; Kerns, E.; Nguyen, K.; Yu, K.R.; Kabir, M.; Williams, J.; Neyra, J.; Southall, N.; Nguyễn, Ð.-T.; et al. Retrospective Assessment of Rat Liver Microsomal Stability at NCATS: Data and QSAR Models. Sci. Rep. 2020, 10, 20713. [Google Scholar] [CrossRef]
  168. Watson, D.J.; Laing, L.; Gibhard, L.; Wong, H.N.; Haynes, R.K.; Wiesner, L. Toward New Transmission-Blocking Combination Therapies: Pharmacokinetics of 10-Amino-Artemisinins and 11-Aza-Artemisinin and Comparison with Dihydroartemisinin and Artemether. Antimicrob. Agents Chemother. 2021, 65, AAC0099021. [Google Scholar] [CrossRef]
  169. Słoczyńska, K.; Gunia-Krzyżak, A.; Koczurkiewicz, P.; Wójcik-Pszczoła, K.; Żelaszczyk, D.; Popiół, J.; Pękala, E. Metabolic Stability and Its Role in the Discovery of New Chemical Entities. Acta Pharm. 2019, 69, 345–361. [Google Scholar] [CrossRef]
  170. Lagardère, P.; Mustière, R.; Amanzougaghene, N.; Hutter, S.; Casanova, M.; Franetich, J.-F.; Tajeri, S.; Malzert-Fréon, A.; Corvaisier, S.; Azas, N.; et al. New Antiplasmodial 4-Amino-Thieno[3,2-d]Pyrimidines with Improved Intestinal Permeability and Microsomal Stability. Eur. J. Med. Chem. 2023, 249, 115115. [Google Scholar] [CrossRef]
  171. Bertram-Ralph, E.; Amare, M. Factors Affecting Drug Absorption and Distribution. Anaesth. Intensive Care Med. 2023, 24, 221–227. [Google Scholar] [CrossRef]
  172. Dorjsuren, D.; Eastman, R.T.; Wicht, K.J.; Jansen, D.; Talley, D.C.; Sigmon, B.A.; Zakharov, A.V.; Roncal, N.; Girvin, A.T.; Antonova-Koch, Y.; et al. Chemoprotective Antimalarials Identified through Quantitative High-Throughput Screening of Plasmodium Blood and Liver Stage Parasites. Sci. Rep. 2021, 11, 2121. [Google Scholar] [CrossRef]
  173. Taft, B.R.; Yokokawa, F.; Kirrane, T.; Mata, A.-C.; Huang, R.; Blaquiere, N.; Waldron, G.; Zou, B.; Simon, O.; Vankadara, S.; et al. Discovery and Preclinical Pharmacology of INE963, a Potent and Fast-Acting Blood-Stage Antimalarial with a High Barrier to Resistance and Potential for Single-Dose Cures in Uncomplicated Malaria. J. Med. Chem. 2022, 65, 3798–3813. [Google Scholar] [CrossRef]
  174. Appetecchia, F.; Fabbrizi, E.; Fiorentino, F.; Consalvi, S.; Biava, M.; Poce, G.; Rotili, D. Transmission-Blocking Strategies for Malaria Eradication: Recent Advances in Small-Molecule Drug Development. Pharmaceuticals 2024, 17, 962. [Google Scholar] [CrossRef]
  175. Lagardère, P.; Mustière, R.; Amanzougaghene, N.; Hutter, S.; Casanova, M.; Franetich, J.-F.; Tajeri, S.; Malzert-Fréon, A.; Corvaisier, S.; Since, M.; et al. Novel Thienopyrimidones Targeting Hepatic and Erythrocytic Stages of Plasmodium Parasites with Increased Microsomal Stability. Eur. J. Med. Chem. 2023, 261, 115873. [Google Scholar] [CrossRef] [PubMed]
  176. Uddin, A.; Gupta, S.; Shoaib, R.; Aneja, B.; Irfan, I.; Gupta, K.; Rawat, N.; Combrinck, J.; Kumar, B.; Aleem, M.; et al. Blood-Stage Antimalarial Activity, Favourable Metabolic Stability and in Vivo Toxicity of Novel Piperazine Linked 7-Chloroquinoline-Triazole Conjugates. Eur. J. Med. Chem. 2024, 264, 115969. [Google Scholar] [CrossRef]
  177. Lim, S.; Lee, S.; Piao, Y.; Choi, M.; Bang, D.; Gu, J.; Kim, S. On Modeling and Utilizing Chemical Compound Information with Deep Learning Technologies: A Task-Oriented Approach. Comput. Struct. Biotechnol. J. 2022, 20, 4288–4304. [Google Scholar] [CrossRef]
  178. Kaur, G.; Grewal, J.; Jyoti, K.; Jain, U.K.; Chandra, R.; Madan, J. Oral Controlled and Sustained Drug Delivery Systems. In Drug Targeting and Stimuli Sensitive Drug Delivery Systems; Elsevier: Amsterdam, The Netherlands, 2018; pp. 567–626. [Google Scholar]
  179. Kok-Yong, S.; Lawrence, L. Drug Distribution and Drug Elimination. In Basic Pharmacokinetic Concepts and Some Clinical Applications; InTech: London, UK, 2015. [Google Scholar]
  180. Liu, X.; Jusko, W.J. Physiologically Based Pharmacokinetics of Lysosomotropic Chloroquine in Rat and Human. J. Pharmacol. Exp. Ther. 2021, 376, 261–272. [Google Scholar] [CrossRef]
  181. Singh, V.; Mambwe, D.; Korkor, C.M.; Chibale, K. Innovation Experiences from Africa-Led Drug Discovery at the Holistic Drug Discovery and Development (H3D) Centre. ACS Med. Chem. Lett. 2022, 13, 1221–1230. [Google Scholar] [CrossRef]
  182. Saadeh, K.; Nantha Kumar, N.; Fazmin, I.T.; Edling, C.E.; Jeevaratnam, K. Anti-malarial Drugs: Mechanisms Underlying Their Proarrhythmic Effects. Br. J. Pharmacol. 2022, 179, 5237–5258. [Google Scholar] [CrossRef]
  183. Kadioglu, O.; Klauck, S.M.; Fleischer, E.; Shan, L.; Efferth, T. Selection of Safe Artemisinin Derivatives Using a Machine Learning-Based Cardiotoxicity Platform and in Vitro and in Vivo Validation. Arch. Toxicol. 2021, 95, 2485–2495. [Google Scholar] [CrossRef]
  184. Achilefu, R.C.; Jumbo, U.K.; Oti, D.C.; Agwaraonye, C.K.; Okezie, O.P.; Anyanwu, W.C. Histopathological Evaluation of the Cardiotoxicity of Dihydroartemisinin-Piperaquine on Male Albino Rats. J. Biosci. Med. 2023, 11, 69–76. [Google Scholar] [CrossRef]
  185. Turkez, H.; Arslan, M.E.; Ozdemir, O. Genotoxicity Testing: Progress and Prospects for the next Decade. Expert Opin. Drug Metab. Toxicol. 2017, 13, 1089–1098. [Google Scholar] [CrossRef]
  186. Gupta, R.; Polaka, S.; Rajpoot, K.; Tekade, M.; Sharma, M.C.; Tekade, R.K. Importance of Toxicity Testing in Drug Discovery and Research. In Pharmacokinetics and Toxicokinetic Considerations; Elsevier: Amsterdam, The Netherlands, 2022; pp. 117–144. [Google Scholar]
  187. Araujo-Lima, C.F.; de Cassia Castro Carvalho, R.; Rosario, S.L.; Leite, D.I.; Aguiar, A.C.C.; de Souza Santos, L.V.; de Araujo, J.S.; Salomão, K.; Kaiser, C.R.; Krettli, A.U.; et al. Antiplasmodial, Trypanocidal, and Genotoxicity In Vitro Assessment of New Hybrid α,α-Difluorophenylacetamide-Statin Derivatives. Pharmaceuticals 2023, 16, 782. [Google Scholar] [CrossRef] [PubMed]
  188. Veeragoni, D.; Deshpande, S.S.; Singh, V.; Misra, S.; Mutheneni, S.R. In Vitro and in Vivo Antimalarial Activity of Green Synthesized Silver Nanoparticles Using Sargassum Tenerrimum—A Marine Seaweed. Acta Trop. 2023, 245, 106982. [Google Scholar] [CrossRef]
  189. Kim, K.; Park, H.; Lim, K.-M. Phototoxicity: Its Mechanism and Animal Alternative Test Methods. Toxicol. Res. 2015, 31, 97–104. [Google Scholar] [CrossRef]
  190. Davis, A.E.; Kennelley, G.E.; Amaye-Obu, T.; Jowdy, P.F.; Ghadersohi, S.; Nasir-Moin, M.; Paragh, G.; Berman, H.A.; Huss, W.J. The Phenomenon of Phototoxicity and Long-Term Risks of Commonly Prescribed and Structurally Diverse Drugs. J. Photochem. Photobiol. 2024, 19, 100221. [Google Scholar] [CrossRef]
  191. Neidle, S. A Phenotypic Approach to the Discovery of Potent G-Quadruplex Targeted Drugs. Molecules 2024, 29, 3653. [Google Scholar] [CrossRef]
  192. Matsumoto, N.; Akimoto, A.; Kawashima, H.; Kim, S. Comparative Study of Skin Phototoxicity with Three Drugs by an in Vivo Mouse Model. J. Toxicol. Sci. 2010, 35, 97–100. [Google Scholar] [CrossRef]
  193. Yadav, N. Pyrimethamine Induces Phototoxicity in Human Keratinocytes via Lysosomal and Mitochondrial Dependent Signaling Pathways under Environmental UVA and UVB Exposure. Toxicology 2022, 479, 153320. [Google Scholar] [CrossRef]
  194. Li, W.; Vazvaei-Smith, F.; Dear, G.; Boer, J.; Cuyckens, F.; Fraier, D.; Liang, Y.; Lu, D.; Mangus, H.; Moliner, P.; et al. Metabolite Bioanalysis in Drug Development: Recommendations from the IQ Consortium Metabolite Bioanalysis Working Group. Clin. Pharmacol. Ther. 2024, 115, 939–953. [Google Scholar] [CrossRef]
  195. Andrade, E.L.; Bento, A.F.; Cavalli, J.; Oliveira, S.K.; Schwanke, R.C.; Siqueira, J.M.; Freitas, C.S.; Marcon, R.; Calixto, J.B. Non-Clinical Studies in the Process of New Drug Development—Part II: Good Laboratory Practice, Metabolism, Pharmacokinetics, Safety and Dose Translation to Clinical Studies. Braz. J. Med. Biol. Res. = Rev. Bras. Pesqui. Medicas e Biol. 2016, 49, e5646. [Google Scholar] [CrossRef]
  196. Koshman, Y.E.; Winters, B.R.; Ryans, J.; Authier, S.; Pugsley, M.K. Maximum Tolerated Dose (MTD) Studies in Drug Toxicology Assessments. In Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays; Springer International Publishing: Cham, Switzerland, 2023; pp. 1–14. [Google Scholar]
  197. Tibon, N.S.; Ng, C.H.; Cheong, S.L. Current Progress in Antimalarial Pharmacotherapy and Multi-Target Drug Discovery. Eur. J. Med. Chem. 2020, 188, 111983. [Google Scholar] [CrossRef] [PubMed]
  198. Bulusu, K.C.; Guha, R.; Mason, D.J.; Lewis, R.P.I.; Muratov, E.; Kalantar Motamedi, Y.; Cokol, M.; Bender, A. Modelling of Compound Combination Effects and Applications to Efficacy and Toxicity: State-of-the-Art, Challenges and Perspectives. Drug Discov. Today 2016, 21, 225–238. [Google Scholar] [CrossRef] [PubMed]
  199. Cheng, F.; Kovács, I.A.; Barabási, A.-L. Network-Based Prediction of Drug Combinations. Nat. Commun. 2019, 10, 1197. [Google Scholar] [CrossRef]
  200. Sacaan, A.; Hashida, S.N.; Khan, N.K. Non-Clinical Combination Toxicology Studies: Strategy, Examples and Future Perspective. J. Toxicol. Sci. 2020, 45, 365–371. [Google Scholar] [CrossRef]
  201. Azri-Meehan, S.; Latriano, L. Repeated-Dose Toxicity Studies in Nonclinical Drug Development. In Nonclinical Safety Assessment; Wiley: Hoboken, NJ, USA, 2013; pp. 197–218. [Google Scholar]
  202. Schultz, T.W.; Cronin, M.T.D. Lessons Learned from Read-across Case Studies for Repeated-Dose Toxicity. Regul. Toxicol. Pharmacol. 2017, 88, 185–191. [Google Scholar] [CrossRef]
  203. Rodrigues-Junior, V.S.; Machado, P.; Calixto, J.B.; Siqueira, J.M.; Andrade, E.L.; Bento, A.F.; Campos, M.M.; Basso, L.A.; Santos, D.S. Preclinical Safety Evaluation of IQG-607 in Rats: Acute and Repeated Dose Toxicity Studies. Regul. Toxicol. Pharmacol. 2017, 86, 11–17. [Google Scholar] [CrossRef]
  204. Denny, K.H. Acute, Subacute, Subchronic, and Chronic General Toxicity Testing for Preclinical Drug Development. In A Comprehensive Guide to Toxicology in Nonclinical Drug Development; Elsevier: Amsterdam, The Netherlands, 2024; pp. 149–171. [Google Scholar]
  205. González, R.; Pons-Duran, C.; Bardají, A.; Leke, R.G.F.; Clark, R.; Menendez, C. Systematic Review of Artemisinin Embryotoxicity in Animals: Implications for Malaria Control in Human Pregnancy. Toxicol. Appl. Pharmacol. 2020, 402, 115127. [Google Scholar] [CrossRef]
  206. El Gaaloul, M.; Tornesi, B.; Lebus, F.; Reddy, D.; Kaszubska, W. Re-Orienting Anti-Malarial Drug Development to Better Serve Pregnant Women. Malar. J. 2022, 21, 121. [Google Scholar] [CrossRef]
  207. Clark, R.L. Safety of Treating Malaria with Artemisinin-Based Combination Therapy in the First Trimester of Pregnancy. Reprod. Toxicol. 2022, 111, 204–210. [Google Scholar] [CrossRef]
  208. Olagunju, A.; Mathad, J.; Eke, A.; Delaney-Moretlwe, S.; Lockman, S. Considerations for the Use of Long-Acting and Extended-Release Agents During Pregnancy and Lactation. Clin. Infect. Dis. 2022, 75, S571–S578. [Google Scholar] [CrossRef]
  209. Rudrapal, M.; Chetia, D. In Vitro and in Vivo Models Used for Antimalarial Activity: A Brief Review. Asian J. Pharm. Pharmacol. 2019, 5, 1251–1255. [Google Scholar] [CrossRef]
  210. Kim, J.; De Jesus, O. Medication Routes of Administration; StatPearls: Treasure Island, FL, USA, 2021. [Google Scholar]
  211. Afolabi, B.B.; Okoromah, C.A. Intramuscular Arteether for Treating Severe Malaria. Cochrane Database Syst. Rev. 2004, 2004, CD004391. [Google Scholar] [CrossRef]
  212. Castelli, F.; Odolini, S.; Autino, B.; Foca, E.; Russo, R. Malaria Prophylaxis: A Comprehensive Review. Pharmaceuticals 2010, 3, 3212–3239. [Google Scholar] [CrossRef]
  213. White, N.J. The Assessment of Antimalarial Drug Efficacy in Vivo. Trends Parasitol. 2022, 38, 660–672. [Google Scholar] [CrossRef]
  214. Fidock, D.A.; Rosenthal, P.J.; Croft, S.L.; Brun, R.; Nwaka, S. Antimalarial Drug Discovery: Efficacy Models for Compound Screening. Nat. Rev. Drug Discov. 2004, 3, 509–520. [Google Scholar] [CrossRef]
  215. Alaribe, S.C.; Oladipupo, A.R.; Uche, G.C.; Onumba, M.U.; Ota, D.; Awodele, O.; Oyibo, W.A. Suppressive, Curative, and Prophylactic Potentials of an Antimalarial Polyherbal Mixture and Its Individual Components in Plasmodium berghei-Infected Mice. J. Ethnopharmacol. 2021, 277, 114105. [Google Scholar] [CrossRef]
  216. Bakshi, R.P.; Tatham, L.M.; Savage, A.C.; Tripathi, A.K.; Mlambo, G.; Ippolito, M.M.; Nenortas, E.; Rannard, S.P.; Owen, A.; Shapiro, T.A. Long-Acting Injectable Atovaquone Nanomedicines for Malaria Prophylaxis. Nat. Commun. 2018, 9, 315. [Google Scholar] [CrossRef]
  217. Siddiqui, A.J.; Bhardwaj, J.; Goyal, M.; Prakash, K.; Adnan, M.; Alreshidi, M.M.; Patel, M.; Soni, A.; Redman, W. Immune Responses in Liver and Spleen against Plasmodium yoelii Pre-Erythrocytic Stages in Swiss Mice Model. J. Adv. Res. 2020, 24, 29–41. [Google Scholar] [CrossRef]
  218. Wang, C.; Zhang, B.; Krüger, A.; Du, X.; Visser, L.; Dömling, A.S.S.; Wrenger, C.; Groves, M.R. Discovery of Small-Molecule Allosteric Inhibitors of Pf ATC as Antimalarials. J. Am. Chem. Soc. 2022, 144, 19070–19077. [Google Scholar] [CrossRef]
  219. Ravindar, L.; Hasbullah, S.A.; Rakesh, K.P.; Hassan, N.I. Pyrazole and Pyrazoline Derivatives as Antimalarial Agents: A Key Review. Eur. J. Pharm. Sci. 2023, 183, 106365. [Google Scholar] [CrossRef]
  220. Nkrumah, D.; Isaac Nketia, R.; Kofi Turkson, B.; Komlaga, G. Malaria: Epidemiology, Life Cycle of Parasite, Control Strategies and Potential Drug Screening Techniques. In Mosquito-Borne Tropical Diseases [Working Title]; IntechOpen: London, UK, 2024. [Google Scholar]
  221. Sinha, S.; Medhi, B.; Radotra, B.D.; Batovska, D.; Markova, N.; Sehgal, R. Evaluation of Chalcone Derivatives for Their Role as Antiparasitic and Neuroprotectant in Experimentally Induced Cerebral Malaria Mouse Model. 3 Biotech 2023, 13, 260. [Google Scholar] [CrossRef]
  222. Radohery, G.F.R.; Walz, A.; Gumpp, C.; Cherkaoui-Rbati, M.H.; Gobeau, N.; Gower, J.; Davenport, M.P.; Rottmann, M.; McCarthy, J.S.; Möhrle, J.J.; et al. Parasite Viability as a Measure of In Vivo Drug Activity in Preclinical and Early Clinical Antimalarial Drug Assessment. Antimicrob. Agents Chemother. 2022, 66, e0011422. [Google Scholar] [CrossRef] [PubMed]
  223. Walz, A.; Sax, S.; Scheurer, C.; Tamasi, B.; Mäser, P.; Wittlin, S. Incomplete Plasmodium falciparum Growth Inhibition Following Piperaquine Treatment Translates into Increased Parasite Viability in the in Vitro Parasite Reduction Ratio Assay. Front. Cell. Infect. Microbiol. 2024, 14, 1396786. [Google Scholar] [CrossRef] [PubMed]
  224. Huang, G.; Murillo Solano, C.; Melendez, J.; Shaw, J.; Collins, J.; Banks, R.; Arshadi, A.K.; Boonhok, R.; Min, H.; Miao, J.; et al. Synthesis, Structure-Activity Relationship, and Antimalarial Efficacy of 6-Chloro-2-Arylvinylquinolines. J. Med. Chem. 2020, 63, 11756–11785. [Google Scholar] [CrossRef]
  225. Le Bihan, A.; de Kanter, R.; Angulo-Barturen, I.; Binkert, C.; Boss, C.; Brun, R.; Brunner, R.; Buchmann, S.; Burrows, J.; Dechering, K.J.; et al. Characterization of Novel Antimalarial Compound ACT-451840: Preclinical Assessment of Activity and Dose–Efficacy Modeling. PLoS Med. 2016, 13, e1002138. [Google Scholar] [CrossRef]
  226. Gilson, P.R.; Nguyen, W.; Poole, W.A.; Teixeira, J.E.; Thompson, J.K.; Guo, K.; Stewart, R.J.; Ashton, T.D.; White, K.L.; Sanz, L.M.; et al. Evaluation of 4-Amino 2-Anilinoquinazolines against Plasmodium and Other Apicomplexan Parasites In Vitro and in a P. falciparum Humanized NOD-Scid IL2Rγ Null Mouse Model of Malaria. Antimicrob. Agents Chemother. 2019, 63. [Google Scholar] [CrossRef]
  227. Edgar, R.C.S.; Malcolm, T.R.; Siddiqui, G.; Giannangelo, C.; Counihan, N.A.; Challis, M.; Duffy, S.; Chowdhury, M.; Marfurt, J.; Dans, M.; et al. On-Target, Dual Aminopeptidase Inhibition Provides Cross-Species Antimalarial Activity. MBio 2024, 15, e0096624. [Google Scholar] [CrossRef]
  228. Chua, M.J.; Tng, J.; Hesping, E.; Fisher, G.M.; Goodman, C.D.; Skinner-Adams, T.; Do, D.; Lucke, A.J.; Reid, R.C.; Fairlie, D.P.; et al. Histone Deacetylase Inhibitor AR-42 and Achiral Analogues Kill Malaria Parasites in Vitro and in Mice. Int. J. Parasitol. Drugs Drug Resist. 2021, 17, 118–127. [Google Scholar] [CrossRef]
  229. Le Manach, C.; Nchinda, A.T.; Paquet, T.; Gonzàlez Cabrera, D.; Younis, Y.; Han, Z.; Bashyam, S.; Zabiulla, M.; Taylor, D.; Lawrence, N.; et al. Identification of a Potential Antimalarial Drug Candidate from a Series of 2-Aminopyrazines by Optimization of Aqueous Solubility and Potency across the Parasite Life Cycle. J. Med. Chem. 2016, 59, 9890–9905. [Google Scholar] [CrossRef]
  230. Gupta, Y.; Sharma, N.; Singh, S.; Romero, J.G.; Rajendran, V.; Mogire, R.M.; Kashif, M.; Beach, J.; Jeske, W.; Poonam; et al. The Multistage Antimalarial Compound Calxinin Perturbates P. falciparum Ca2+ Homeostasis by Targeting a Unique Ion Channel. Pharmaceutics 2022, 14, 1371. [Google Scholar] [CrossRef]
  231. Abay, E.T.; van der Westuizen, J.H.; Swart, K.J.; Gibhard, L.; Lawrence, N.; Dambuza, N.; Wilhelm, A.; Pravin, K.; Wiesner, L. Efficacy and Pharmacokinetic Evaluation of a Novel Anti-Malarial Compound (NP046) in a Mouse Model. Malar. J. 2015, 14, 8. [Google Scholar] [CrossRef]
  232. Moreno-Sabater, A.; Pérignon, J.L.; Mazier, D.; Lavazec, C.; Soulard, V. Humanized Mouse Models Infected with Human Plasmodium Species for Antimalarial Drug Discovery. Expert Opin. Drug Discov. 2018, 13, 131–140. [Google Scholar] [CrossRef] [PubMed]
  233. De-Oliveira, A.C.A.X.; Paumgartten, F.J.R. Malaria-Induced Alterations of Drug Kinetics and Metabolism in Rodents and Humans. Curr. Drug Metab. 2021, 22, 127–138. [Google Scholar] [CrossRef]
  234. Demarta-Gatsi, C.; Andenmatten, N.; Jiménez-Díaz, M.B.; Gobeau, N.; Cherkaoui-Rabti, M.H.; Fuchs, A.; Díaz, P.; Berja, S.; Sánchez, R.; Gómez, H.; et al. Predicting Optimal Antimalarial Drug Combinations from a Standardized Plasmodium falciparum Humanized Mouse Model. Antimicrob. Agents Chemother. 2023, 67, e0157422. [Google Scholar] [CrossRef]
Figure 1. Antimalarial drug discovery workflow.
Figure 1. Antimalarial drug discovery workflow.
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Figure 2. Drug development pipeline.
Figure 2. Drug development pipeline.
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Figure 3. In vivo pharmacokinetic parameters in antimalarial drug discovery.
Figure 3. In vivo pharmacokinetic parameters in antimalarial drug discovery.
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Figure 4. In vivo safety parameters in drug discovery.
Figure 4. In vivo safety parameters in drug discovery.
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Figure 5. In vivo efficacy parameters in antimalarial drug discovery.
Figure 5. In vivo efficacy parameters in antimalarial drug discovery.
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Table 4. Some antimalarial leads, with their in vivo efficacy assessment and their murine model.
Table 4. Some antimalarial leads, with their in vivo efficacy assessment and their murine model.
Lead CompoundsIn Vivo EfficacyMurine ModelReference
UCF501Curative BALB/c/Swiss Webster [224]
ACT-451840CurativeNMRI[225]
WEB-484, WEB-485, WEB-486, WEB-487Suppressive NOD-scid IL2Rγnull[226]
INE963CurativeNOD-scid IL-2Rγnull[173]
MMV1557817SuppressiveBalb/c/Swiss Outbred[227]
AR-42CurativeBALB/c[228]
UCT943SuppressiveNOD-scid IL-2Rγnull[229]
CalxininSuppressiveC57BL6[230]
NP046SuppressiveC57BL/6[231]
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Adebayo, G.; Ayanda, O.I.; Rottmann, M.; Ajibaye, O.S.; Oduselu, G.; Mulindwa, J.; Ajani, O.O.; Aina, O.; Mäser, P.; Adebiyi, E. The Importance of Murine Models in Determining In Vivo Pharmacokinetics, Safety, and Efficacy in Antimalarial Drug Discovery. Pharmaceuticals 2025, 18, 424. https://doi.org/10.3390/ph18030424

AMA Style

Adebayo G, Ayanda OI, Rottmann M, Ajibaye OS, Oduselu G, Mulindwa J, Ajani OO, Aina O, Mäser P, Adebiyi E. The Importance of Murine Models in Determining In Vivo Pharmacokinetics, Safety, and Efficacy in Antimalarial Drug Discovery. Pharmaceuticals. 2025; 18(3):424. https://doi.org/10.3390/ph18030424

Chicago/Turabian Style

Adebayo, Glory, Opeyemi I. Ayanda, Matthias Rottmann, Olusola S. Ajibaye, Gbolahan Oduselu, Julius Mulindwa, Olayinka O. Ajani, Oluwagbemiga Aina, Pascal Mäser, and Ezekiel Adebiyi. 2025. "The Importance of Murine Models in Determining In Vivo Pharmacokinetics, Safety, and Efficacy in Antimalarial Drug Discovery" Pharmaceuticals 18, no. 3: 424. https://doi.org/10.3390/ph18030424

APA Style

Adebayo, G., Ayanda, O. I., Rottmann, M., Ajibaye, O. S., Oduselu, G., Mulindwa, J., Ajani, O. O., Aina, O., Mäser, P., & Adebiyi, E. (2025). The Importance of Murine Models in Determining In Vivo Pharmacokinetics, Safety, and Efficacy in Antimalarial Drug Discovery. Pharmaceuticals, 18(3), 424. https://doi.org/10.3390/ph18030424

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