**4. Comparative Analysis**

Based on the literature survey, Table 1 below presents the domains, the purposes, the broad areas of application, and the core advantages related to BD.


**Table 1.** Summary of BD in Pharmacology, Toxicology and Pharmaceutics.


**Table 1.** *Cont*.

## **5. Critical Analysis**

The critical analysis was conducted with the aim of tracing which particular field has implemented BD. The results of the critical analysis are graphically represented in Figure 5.

**Figure 5.** Analysis of BD implementation in Pharmacology, Toxicology and Pharmaceutics.

From Figure 5, it is clear that the pharmacology sector is observed to employ BD more than the other two fields. This is because this sector produces more data while developing drugs for the identified chronic diseases. Additionally, through extensive research, it has been found that very few researchers have attempted to conduct research on the implementations of BD in the considered fields. Therefore, it might be more beneficial for the medicinal community to have investigators attempt to execute research regarding the technical implementation of BD in the drug development sector.

#### **6. Limitations of BD**

The limitations of BD include cases where the quality of the data is compromised and when the users fail to utilise BD analytics approaches correctly. In addition, certain other limitations are discussed in this section.

The main limitation of BD is mostly associated with the quality of data. The main determinant of this aspect is completely dependent on the source of the data. In addition, the managemen<sup>t</sup> and storage of data also play a vital role in the characteristics of the data. Some significant features regarding data quality are data completeness, accuracy, and adequacy. The modification of these features may pose a threat to users, especially when using BD, as it can endanger the integrity of the associated results of the analysis [51]. Thus, BD is said to return inaccurate results due to corruption of the quality of the data, resulting from the generation of false assumptions. These false assumptions might produce weak knowledge with large errors. This does not result only from the data quality, but also the data selection approach and the sample size. Large data sets with a high number of attributes can enable statistically significant results to be obtained; however, on the other hand, due to the huge data size, users may choose data arbitrarily while neglecting information regarding the data representativeness, resulting in selection bias. In both cases, the results and the accuracy of a BD-based approach might be compromised [51].

These aforementioned limitations also involve the user. It is significant to understand when to implement BD to resolve certain issues. Users should be well-aware of the features of the data and perceive compatibility among the data sets to obtain an appropriate and beneficial analysis, and should be well-aware of the underlying difficulties that arise when data are compared within domains without similar features and attributes [60]. To correctly utilise BD analytics, the main objectives and implementation results should be understood a priori. Additionally, users should educate themselves, in order to understand the possible mechanism(s) behind the researched phenomenon or object, in order to hypothesise the possible results. Finally, they should estimate the outcomes with the presumed objective at the initial step. If the users neglect or commit any mistakes in the steps above, the BD mechanism will likely produce erroneous results [60].


**Table 2.** Challenges and future directions.

Based on the summary presented in Table 2, future research lines to address the existing challenges may be gleaned to take the domain in new directions, helping to advance the considered fields and, thereby, indirectly helping to better humankind.

#### **7. Conclusions and Discussion**

The pharmaceutical industry is facing a challenge in productivity, and BD initiatives may provide the insights necessary to turn the industry around. Considering this, the present study detailed a substantial attempt to review the existing literature regarding the implementation of BD in the pharmacology, pharmaceutics, and toxicology sectors. The pharmacology, toxicology, and pharmaceutics fields are still in the early stage of BD adoption. Additionally, according to the critical analysis, the pharmacology sector has employed BD more than the other two sectors. Based on our survey, the key inferences were as follows: first, BD can help researchers better understand the effects of drugs and other chemicals on the human body, which can help to improve the safety and efficacy of drugs and other chemicals; second, BD can help to improve the accuracy of predictions regarding the effects of drugs and chemicals, which can improve safety in drug development and help to avoid potential adverse drug interactions; finally, BD can help improve our understanding of how the body metabolises drugs and other chemicals, which can improve the safety and efficacy of drugs and other chemicals. The domains considered in our survey are ultimately necessary for humanity, and BD may significantly impact the betterment of these domains. BD has revolutionary potential, providing new ways to understand and predict the effects of drugs. However, BD in this domain also poses new challenges, which should be taken up as key research problems. Despite these challenges, in the future, BD will likely play an important role in pharmacology, toxicology, and pharmaceutics, critically helping to improve drug safety and efficacy.

**Author Contributions:** Review design, Ideation, initial draft, figure illustration and conceptualization, K.L.B.; literature curation, review and editing, R.S.O., E.D.G.; Additional illustration, additional data curation E.Y.A.; Improve the presentation, validation and restructuring of the manuscript, C.A.; Proofreading the manuscript and improvements, E.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.
