Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Antibiotics antibiotics	4.3	7.3	2012	15.8 Days	CHF 2900	Submit
Journal of Personalized Medicine jpm	-	4.1	2011	17.4 Days	CHF 2600	Submit
Pharmaceuticals pharmaceuticals	4.3	6.1	2004	13.9 Days	CHF 2900	Submit
Pharmaceutics pharmaceutics	4.9	7.9	2009	15.5 Days	CHF 2900	Submit
Medicines medicines	-	-	2014	28.6 Days	CHF 1400	Submit

11 pages, 941 KiB

Open AccessArticle

Auto-Induction in Oral Esketamine Treatment for Treatment-Resistant Depression: An Exploratory Study

by Jolien K. E. Veraart, Cornelis F. Vos, Nieko C. Punt, Dylan Visser, Mireille A. Wessels, Sanne Y. Smith-Apeldoorn, Jeanine Kamphuis, Robert A. Schoevers and Daan J. Touw

Pharmaceuticals 2025, 18(5), 627; https://doi.org/10.3390/ph18050627 (registering DOI) - 25 Apr 2025

Abstract

Background: Esketamine is a rapidly acting antidepressant with robust efficacy in treatment-resistant depression (TRD). Diminishing therapeutic effects and attenuated side effects have been reported after long-term use. This study aimed to investigate its long-term pharmacokinetics and factors that may contribute to reduced efficacy [...] Read more.

Background: Esketamine is a rapidly acting antidepressant with robust efficacy in treatment-resistant depression (TRD). Diminishing therapeutic effects and attenuated side effects have been reported after long-term use. This study aimed to investigate its long-term pharmacokinetics and factors that may contribute to reduced efficacy over time in patients with TRD by evaluating the potential role of auto-induction. Methods: Pharmacokinetic data were collected from 18 patients receiving oral esketamine for six weeks. A pharmacokinetic model was developed to predict esketamine and noresketamine plasma concentrations. Observed esketamine and noresketamine plasma concentrations were compared to model-predicted concentrations to assess deviations suggestive of auto-induction. Results: On day 39, plasma concentrations of esketamine and noresketamine were 59% and 35% lower than predicted, respectively, indicative of auto-induction of CYP3A4 and CYP2B6. Conclusions: Auto-induction appears to occur in oral esketamine treatment, which may contribute to reduced therapeutic efficacy and side effects in long-term treatment. Identifying auto-induction as a mechanism of tolerance potentially has important clinical implications. Further studies are warranted to confirm these findings and evaluate strategies to maintain therapeutic efficacy. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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18 pages, 3907 KiB

Open AccessArticle

Model-Informed Dose Optimization of Spironolactone in Neonates and Infants

by Amira Soliman, Leandro F. Pippa, Jana Lass, Stephanie Leroux, Valvanera Vozmediano and Natalia V. de Moraes

Pharmaceuticals 2025, 18(3), 355; https://doi.org/10.3390/ph18030355 - 1 Mar 2025

Viewed by 963

Abstract

Background/Objectives: Spironolactone (SP) has been used off-label in pediatrics since its approval, but its use is challenged by limited pharmacokinetic (PK) data in adults and especially in children. Methods: Physiologically based pharmacokinetic (PBPK) models for SP and its active metabolites, canrenone [...] Read more.

Background/Objectives: Spironolactone (SP) has been used off-label in pediatrics since its approval, but its use is challenged by limited pharmacokinetic (PK) data in adults and especially in children. Methods: Physiologically based pharmacokinetic (PBPK) models for SP and its active metabolites, canrenone (CAN) and 7α thio-methyl spironolactone (TMS), in adults were developed. These models aim to enhance understanding of SP’s PK and provide a basis for predicting PK and optimizing SP dosing in infants and neonates. Given SP’s complex metabolism, we assumed complete conversion to CAN and TMS by CES1 enzymes, fitting CES1-mediated metabolism to the parent-metabolite model using PK data. We incorporated ontogeny for CES1 and CYP3A4 and other age-related physiological changes into the model to anticipate PK in the pediatric population. Results: The PBPK models for SP, CAN, and TMS accurately captured the observed PK data in healthy adults across various dosing regimens, including the impact of food on drug exposure. The pediatric PBPK model was evaluated using PK data from infants and neonates. Simulations indicate that 2.5 mg/kg in 6-month to 2-year infants and 2 mg/kg in 1–6-months infants matched the total unbound systemic exposure equivalent to the standard recommended daily maintenance dose of 100 mg in adults for treating edema. Conclusions: The developed PBPK model provides valuable insights for dosing decisions and optimizing therapeutic outcomes, especially in populations where clinical studies are challenging. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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20 pages, 4804 KiB

Open AccessArticle

Key Factors for Improving Predictive Accuracy and Avoiding Overparameterization of the PBPK Absorption Model in Food Effect Studies of Weakly Basic Water-Insoluble Compounds in Immediate Release Formulations

by Miao Zhang, Shudong Zhang, Lin Wang, Zhe Zhang, Qin Hu and Dongyang Liu

Pharmaceutics 2024, 16(10), 1324; https://doi.org/10.3390/pharmaceutics16101324 - 12 Oct 2024

Cited by 3 | Viewed by 1611

Abstract

Background/Objectives: Physiologically based pharmacokinetic (PBPK) absorption models are instrumental for assessing drug absorption prior to clinical food effect studies, though discrepancies in predictive and actual outcomes are observed. This study focused on immediate release formulations of weakly basic water-insoluble compounds, namely rivaroxaban, [...] Read more.

Background/Objectives: Physiologically based pharmacokinetic (PBPK) absorption models are instrumental for assessing drug absorption prior to clinical food effect studies, though discrepancies in predictive and actual outcomes are observed. This study focused on immediate release formulations of weakly basic water-insoluble compounds, namely rivaroxaban, ticagrelor, and PB-201, to investigate factors that could improve the predictive accuracy of PBPK models regarding food effects. Methods: Comprehensive in vitro experimental results provided the basis for the development of mechanistic absorption models, which were then combined with mechanistic disposition models to predict the systemic exposure of the model drugs in both fasted and fed states. Results: The developed PBPK models showed moderate to high predictive accuracy for food effects in Caucasian populations. For the Chinese population, the ticagrelor model’s initial overestimation of fed-state absorption was addressed by updating the permeability parameters from Caco-2 cell assays to those derived from parallel artificial membrane permeability assays in FaSSIF and FeSSIF media. This refinement was also applied to the rivaroxaban and ticagrelor models, leading to a more accurate representation of absorption in Caucasians. Conclusions: This study highlights the importance of apparent permeability in enhancing the predictive accuracy of PBPK absorption models for weakly basic water-insoluble compounds. Furthermore, the precipitation of PB-201 in the two-stage transfer experiments suggests that precipitation may not be a universal phenomenon for such compounds in vivo. Consequently, the precipitation rate constant, a theoretically essential parameter, should be determined based on experimental evidence to avoid overparameterization and ensure robust predictive accuracy of PBPK models. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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14 pages, 3310 KiB

Open AccessArticle

Dosing Evaluation of Ceftazidime–Avibactam in Intensive Care Unit Patients Based on Pharmacokinetic/Pharmacodynamic (PK/PD) Modeling and Simulation

by Hinojal Zazo, Yuridia Aguazul and José M. Lanao

Antibiotics 2024, 13(9), 861; https://doi.org/10.3390/antibiotics13090861 - 9 Sep 2024

Viewed by 1428

Abstract

P. aeruginosa is the most common microorganism involved in many ICU-acquired infections. A correct dosage regimen is pivotal to avoiding resistance development, worse outcomes and higher mortality rates. The aim of this study was to perform a pharmacokinetic–pharmacodynamic (PK/PD) evaluation of recommended dosing [...] Read more.

P. aeruginosa is the most common microorganism involved in many ICU-acquired infections. A correct dosage regimen is pivotal to avoiding resistance development, worse outcomes and higher mortality rates. The aim of this study was to perform a pharmacokinetic–pharmacodynamic (PK/PD) evaluation of recommended dosing regimens of ceftazidime–avibactam (CAZ–AVI) in ICU patients with different degrees of renal function for a specific strain of Pseudomonas aeruginosa. A semi-mechanistic PK/PD model has been developed. It allows for the simulation of CAZ–AVI steady-state plasma level curves and the evolution of bacterial growth curves. The percentage of bacterial load reduction and the value of the recommended PK/PD indices have been taken into account to define the success or failure of the regimens. Probabilistic analysis was performed using Monte Carlo simulations of two populations: control and ICU. In both populations, dosing regimens endorsed for patients with CLcr higher than 10 mL/min reach the PK/PD indices recommended, T > MIC > 90% and Cmin/MIC > 1.3. While dosage regimens endorsed for patients with CLcr of 10 mL/min or lower fail (T > MIC < 60% and Cmin/MIC < 0.35). However, proposed dosing regimens based on shortening dosing intervals for these patients would be successful, increasing bacterial load reduction by almost 50% and reaching the proposed PK/PD indices. Therefore, CAZ–AVI dosing strategies based on model-informed precision dosing (MIPD) could directly influence the efficacy of results in ICU patients with renal insufficiency. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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15 pages, 1626 KiB

Open AccessArticle

Population Pharmacokinetic–Pharmacodynamic Analysis of a Reserpine-Induced Myalgia Model in Rats

by Gloria M. Alfosea-Cuadrado, Javier Zarzoso-Foj, Albert Adell, Alfonso A. Valverde-Navarro, Eva M. González-Soler, Víctor Mangas-Sanjuán and Arantxa Blasco-Serra

Pharmaceutics 2024, 16(8), 1101; https://doi.org/10.3390/pharmaceutics16081101 - 21 Aug 2024

Cited by 1 | Viewed by 1654

Abstract

(1) Background: Fibromyalgia syndrome (FMS) is a chronic pain condition with widespread pain and multiple comorbidities, for which conventional therapies offer limited benefits. The reserpine-induced myalgia (RIM) model is an efficient animal model of FMS in rodents. This study aimed to develop a [...] Read more.

(1) Background: Fibromyalgia syndrome (FMS) is a chronic pain condition with widespread pain and multiple comorbidities, for which conventional therapies offer limited benefits. The reserpine-induced myalgia (RIM) model is an efficient animal model of FMS in rodents. This study aimed to develop a pharmacokinetic–pharmacodynamic (PK–PD) model of reserpine in rats, linking to its impact on monoamines (MAs). (2) Methods: Reserpine was administered daily for three consecutive days at dose levels of 0.1, 0.5, and 1 mg/kg. A total of 120 rats were included, and 120 PK and 828 PD observations were collected from 48 to 96 h after the first dose of reserpine. Non-linear mixed-effect data analysis was applied for structural PK–PD model definition, variability characterization, and covariate analysis. (3) Results: A one-compartment model best described reserpine in rats (V = 1.3 mL/kg and CL = 4.5 × 10⁻¹ mL/h/kg). A precursor-pool PK–PD model (k_in = 6.1 × 10⁻³ mg/h, k_p = 8.6 × 10⁻⁴ h⁻¹ and k_out = 2.7 × 10⁻² h⁻¹) with a parallel transit chain (k₀ = 1.9 × 10⁻¹ h⁻¹) characterized the longitudinal levels of MA in the prefrontal cortex, spinal cord, and amygdala in rats. Reserpine stimulates the degradation of MA from the pool compartment (Slope₁ = 1.1 × 10⁻¹ h) and the elimination of MA (Slope₂ = 1.25 h) through the transit chain. Regarding the reference dose (1 mg/kg) of the RIM model, the administration of 4 mg/kg would lead to a mean reduction of 65% (C_max), 80% (C_min), and 70% (AUC) of MA across the brain regions tested. (4) Conclusions: Regional brain variations in neurotransmitter depletion were identified, particularly in the amygdala, offering insights for therapeutic strategies and biomarker identification in FMS research. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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12 pages, 1786 KiB

Open AccessArticle

Development and Evaluation of a Quantitative Systems Pharmacology Model for Mechanism Interpretation and Efficacy Prediction of Atezolizumab in Combination with Carboplatin and Nab-Paclitaxel in Patients with Non-Small-Cell Lung Cancer

by Chen-Yu Wang, Hao-Ran Dai, Yu-Ping Tan, Di-Hong Yang, Xiao-Min Niu, Lu Han, Wen Wang, Ling-Ling Ma, Aleksi Julku and Zheng Jiao

Pharmaceuticals 2024, 17(2), 238; https://doi.org/10.3390/ph17020238 - 12 Feb 2024

Cited by 1 | Viewed by 2755

Abstract

Immunotherapy has shown clinical benefit in patients with non-small-cell lung cancer (NSCLC). Due to the limited response of monotherapy, combining immune checkpoint inhibitors (ICIs) and chemotherapy is considered a treatment option for advanced NSCLC. However, the mechanism of combined therapy and the potential [...] Read more.

Immunotherapy has shown clinical benefit in patients with non-small-cell lung cancer (NSCLC). Due to the limited response of monotherapy, combining immune checkpoint inhibitors (ICIs) and chemotherapy is considered a treatment option for advanced NSCLC. However, the mechanism of combined therapy and the potential patient population that could benefit from combined therapy remain undetermined. Here, we developed an NSCLC model based on the published quantitative systems pharmacology (QSP)-immuno-oncology platform by making necessary adjustments. After calibration and validation, the established QSP model could adequately characterise the biological mechanisms of action of the triple combination of atezolizumab, nab-paclitaxel, and carboplatin in patients with NSCLC, and identify predictive biomarkers for precision dosing. The established model could efficiently characterise the objective response rate and duration of response of the IMpower131 trial, reproducing the efficacy of alternative dosing. Furthermore, CD8+ and CD4+ T cell densities in tumours were found to be significantly related to the response status. This significant extension of the QSP model not only broadens its applicability but also more accurately reflects real-world clinical settings. Importantly, it positions the model as a critical foundation for model-informed drug development and the customisation of treatment plans, especially in the context of combining single-agent ICIs with platinum-doublet chemotherapy. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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13 pages, 1995 KiB

Open AccessArticle

Population Pharmacodynamic Models of Risperidone on PANSS Total Scores and Prolactin Levels in Schizophrenia

by Zhiwei Huang, Lei Zhang, Yan Li, Yimin Yu, Yifeng Shen, Xiujia Sun, Kun Lou, Hongmei Luo, Zhibin Meng, Huafang Li and Yumei Wei

Pharmaceuticals 2024, 17(2), 148; https://doi.org/10.3390/ph17020148 - 23 Jan 2024

Viewed by 1703

Abstract

Currently, research predominantly focuses on evaluating clinical effects at specific time points while neglecting underlying patterns within the treatment process. This study aims to analyze the dynamic alterations in PANSS total scores and prolactin levels in patients with schizophrenia treated with risperidone, along [...] Read more.

Currently, research predominantly focuses on evaluating clinical effects at specific time points while neglecting underlying patterns within the treatment process. This study aims to analyze the dynamic alterations in PANSS total scores and prolactin levels in patients with schizophrenia treated with risperidone, along with the influencing covariates. Using data from an 8-week randomized, double-blind, multicenter clinical trial, a population pharmacodynamic model was established for the PANSS total scores of and prolactin levels in patients treated with risperidone. The base model employed was the E_max model. Covariate selection was conducted using a stepwise forward inclusion and backward elimination approach. A total of 144 patients were included in this analysis, with 807 PANSS total scores and 531 prolactin concentration values. The PANSS total scores of the patients treated with risperidone decreased over time, fitting a proportionally parameterized sigmoid E_max model with covariates including baseline score, course of the disease, gender, plasma calcium ions, and lactate dehydrogenase levels. The increase in prolactin levels conformed to the ordinary E_max model, with covariates encompassing course of the disease, gender, weight, red blood cell count, and triglyceride levels. The impacts of the baseline scores and the course of the disease on the reduction of the PANSS scores, as well as the influence of gender on the elevation of prolactin levels, each exceeded 20%. This study provides valuable quantitative data regarding PANSS total scores and prolactin levels among patients undergoing risperidone treatment across various physiological conditions. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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10 pages, 243 KiB

Open AccessBrief Report

Animal Models in Regulatory Breakpoint Determination: Review of New Drug Applications of Approved Antibiotics from 2014–2022

by Daniel Selig, Diana Caridha, Martin Evans, Adrian Kress, Charlotte Lanteri, Roseanne Ressner and Jesse DeLuca

J. Pers. Med. 2024, 14(1), 111; https://doi.org/10.3390/jpm14010111 - 19 Jan 2024

Viewed by 1809

Abstract

We sought to better understand the utility and role of animal models of infection for Food and Drug Administration (FDA)-approved antibiotics for the indications of community-, hospital-acquired-, and ventilator-associated bacterial pneumonia (CABP, HABP, VABP), complicated urinary tract infection (cUTI), complicated intra-abdominal infection (cIAI), [...] Read more.

We sought to better understand the utility and role of animal models of infection for Food and Drug Administration (FDA)-approved antibiotics for the indications of community-, hospital-acquired-, and ventilator-associated bacterial pneumonia (CABP, HABP, VABP), complicated urinary tract infection (cUTI), complicated intra-abdominal infection (cIAI), and acute bacterial skin and structural infections (ABSSSIs). We reviewed relevant documents from new drug applications (NDA) of FDA-approved antibiotics from 2014–2019 for the above indications. Murine neutropenic thigh infection models supported the choice of a pharmacokinetic-pharmacodynamic (PKPD) target in 11/12 NDAs reviewed. PKPD targets associated with at least a 1-log bacterial decrease were commonly considered ideal (10/12 NDAs) to support breakpoints. Plasma PK, as opposed to organ specific PK, was generally considered most reliable for PKPD correlation. Breakpoint determination was multi-disciplinary, accounting at minimum for epidemiologic cutoffs, non-clinical PKPD, clinical exposure-response and clinical efficacy. Non-clinical PKPD targets in combination with probability of target attainment (PTA) analyses generated breakpoints that were consistent with epidemiologic cutoffs and clinically derived breakpoints. In 6/12 NDAs, there was limited data to support clinically derived breakpoints, and hence the non-clinical PKPD targets in combination with PTA analyses played a heightened role in the final breakpoint determination. Sponsor and FDA breakpoint decisions were in general agreement. Disagreement may have arisen from differences in the definition of the optimal PKPD index or the ability to extrapolate protein binding from animals to humans. Overall, murine neutropenic thigh infection models supported the reviewed NDAs by providing evidence of pre-clinical efficacy and PKPD target determination, and played, in combination with PTA analysis, a significant role in breakpoint determination for labeling purposes. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

11 pages, 2411 KiB

Open AccessArticle

A Pharmacodynamic Study of Aminoglycosides against Pathogenic E. coli through Monte Carlo Simulation

by Eon-Bee Lee and Kyubae Lee

Pharmaceuticals 2024, 17(1), 27; https://doi.org/10.3390/ph17010027 - 24 Dec 2023

Cited by 1 | Viewed by 2488

Abstract

This research focuses on combating the increasing problem of antimicrobial resistance, especially in Escherichia coli (E. coli), by assessing the efficacy of aminoglycosides. The study specifically addresses the challenge of developing new therapeutic approaches by integrating experimental data with mathematical modeling [...] Read more.

This research focuses on combating the increasing problem of antimicrobial resistance, especially in Escherichia coli (E. coli), by assessing the efficacy of aminoglycosides. The study specifically addresses the challenge of developing new therapeutic approaches by integrating experimental data with mathematical modeling to better understand the action of aminoglycosides. It involves testing various antibiotics like streptomycin (SMN), kanamycin (KMN), gentamicin (GMN), tobramycin (TMN), and amikacin (AKN) against the O157:H7 strain of E. coli. The study employs a pharmacodynamics (PD) model to analyze how different antibiotic concentrations affect bacterial growth, utilizing minimum inhibitory concentration (MIC) to gauge the effective bactericidal levels of the antibiotics. The study’s approach involved transforming bacterial growth rates, as obtained from time–kill curve data, into logarithmic values. A model was then developed to correlate these log-transformed values with their respective responses. To generate additional data points, each value was systematically increased by an increment of 0.1. To simulate real-world variability and randomness in the data, a Gaussian scatter model, characterized by parameters like κ and EC₅₀, was employed. The mathematical modeling was pivotal in uncovering the bactericidal properties of these antibiotics, indicating different PD MIC (zMIC) values for each (SMN: 1.22; KMN: 0.89; GMN: 0.21; TMN: 0.32; AKN: 0.13), which aligned with MIC values obtained through microdilution methods. This innovative blend of experimental and mathematical approaches in the study marks a significant advancement in formulating strategies to combat the growing threat of antimicrobial-resistant E. coli, offering a novel pathway to understand and tackle antimicrobial resistance more effectively. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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27 pages, 6909 KiB

Open AccessArticle

Enhancement of Skin Permeability Prediction through PBPK Modeling, Bayesian Inference, and Experiment Design

by Abdullah Hamadeh, Abdulkarim Najjar, John Troutman and Andrea Edginton

Pharmaceutics 2023, 15(12), 2667; https://doi.org/10.3390/pharmaceutics15122667 - 24 Nov 2023

Cited by 1 | Viewed by 1770

Abstract

Physiologically based pharmacokinetic (PBPK) models of skin absorption are a powerful resource for estimating drug delivery and chemical risk of dermatological products. This paper presents a PBPK workflow for the quantification of the mechanistic determinants of skin permeability and the use of these [...] Read more.

Physiologically based pharmacokinetic (PBPK) models of skin absorption are a powerful resource for estimating drug delivery and chemical risk of dermatological products. This paper presents a PBPK workflow for the quantification of the mechanistic determinants of skin permeability and the use of these quantities in the prediction of skin absorption in novel contexts. A state-of-the-art mechanistic model of dermal absorption was programmed into an open-source modeling framework. A sensitivity analysis was performed to identify the uncertain compound-specific, individual-specific, and site-specific model parameters that impact permeability. A Bayesian Markov Chain Monte Carlo algorithm was employed to derive distributions of these parameters given in vitro experimental permeability measurements. Extrapolations to novel contexts were generated by simulating the model following its update with samples drawn from the learned distributions as well as parameters that represent the intended scenario. This algorithm was applied multiple times, each using a unique set of permeability measurements sourced under experimental contexts that differ in terms of the compound, vehicle pH, skin sample anatomical site, and the number of compounds under which each subject’s skin samples were tested. Among the data sets used in this study, the highest accuracy and precision in the extrapolated permeability was achieved in those that include measurements conducted under multiple vehicle pH levels and in which individual subjects’ skin samples are tested under multiple compounds. This work thus identifies factors for consideration in the design of experiments for the purpose of training dermal models to robustly estimate drug delivery and chemical risk. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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53 pages, 1613 KiB

Open AccessReview

A Critical Analysis of the FDA’s Omics-Driven Pharmacodynamic Biomarkers to Establish Biosimilarity

by Sarfaraz K. Niazi

Pharmaceuticals 2023, 16(11), 1556; https://doi.org/10.3390/ph16111556 - 2 Nov 2023

Cited by 4 | Viewed by 3318

Abstract

Demonstrating biosimilarity entails comprehensive analytical assessment, clinical pharmacology profiling, and efficacy testing in patients for at least one medical indication, as required by the U.S. Biologics Price Competition and Innovation Act (BPCIA). The efficacy testing can be waived if the drug has known [...] Read more.

Demonstrating biosimilarity entails comprehensive analytical assessment, clinical pharmacology profiling, and efficacy testing in patients for at least one medical indication, as required by the U.S. Biologics Price Competition and Innovation Act (BPCIA). The efficacy testing can be waived if the drug has known pharmacodynamic (PD) markers, leaving most therapeutic proteins out of this concession. To overcome this, the FDA suggests that biosimilar developers discover PD biomarkers using omics technologies such as proteomics, glycomics, transcriptomics, genomics, epigenomics, and metabolomics. This approach is redundant since the mode-action-action biomarkers of approved therapeutic proteins are already available, as compiled in this paper for the first time. Other potential biomarkers are receptor binding and pharmacokinetic profiling, which can be made more relevant to ensure biosimilarity without requiring biosimilar developers to conduct extensive research, for which they are rarely qualified. Full article

(This article belongs to the Topic Pharmacokinetic and Pharmacodynamic Modelling in Drug Discovery and Development)

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