World Journal of Pharmacology and Toxicology
Open Access

Drug discovery and development; New drug application; Biologics license application; Pharmacokinetics; ADME; New modalities; Model-informed drug development

Introduction

Drug metabolism and pharmacokinetics (DMPK) is conventionally known as a scientific discipline that studies the availability of drugs or drug candidates for pharmacological processes and characterizes their entry (absorption) into the body, fate within the body (including distribution and biotransformation), and elimination from the body, overtime. The basic research into DMPK mechanisms has been the driving force for advancement in a number of scientific areas, such as the biochemistry, pharmacology, and genetics of drug-metabolizing enzymes (DMEs) and transporters, as well as their regulators [1]. The translation of the new knowledge and technical development in basic DMPK science, carried out by researchers from academia, pharmaceutical industry, and regulatory agencies, has played essential roles in the success of the pharmaceutical sciences field in developing new therapies for numerous human diseases and will remain so for the continued quest for discovering and developing better drugs in shorter time frames [2]. The overall process of drug discovery and development can be divided into six stages: hit to lead, lead optimization, candidate selection, preclinical development, clinical development, registration and launch and post-marketing surveillance [3]. The processes of studying and characterizing ADME-PK properties have been well recognized as an integral discipline, which are indispensable and permeate all phases of the drug discovery and development pipeline. Prior to 2000s, the focus of DMPK scientists in the pharmaceutical industry is primarily to provide a descriptive characterization for drug candidates in support of clinical trials and regulatory registration. Over the past decade, numerous high throughput tools have been adapted in pharmaceutical industry that enables a large volume of compounds entering the ADME testing funnels [4]. However, the high throughput screening did not shorten the time of drug discovery from the bench to bedside; rather, the paradigm of DMPK inquiries has been dramatically shifted by the advances in related fields, such as pharmacogenetics, pharmacogenomics and the functional characterization of various drug transporters located in different organs, to focusing on gaining a more quantitative and mechanistic understanding of the fate of drug candidates in biological systems [5]. Consequently, unprecedented insights can now be obtained on the molecular and mechanistic bases of the potential for drug–drug interactions (DDIs), interindividual variability of drug exposure, and asymmetric exposure in key organs either on or off the intended drug targets. As such, the discipline is well integrated into the holistic drug discovery paradigm to optimize ADME properties of molecules early and select drug candidates for entry into development [6].

Discussion

Drug discovery and development is a complex and time-consuming process that involves various stages, including target identification, lead optimization, preclinical testing, and clinical trials. In recent years, the integration of drug metabolism and pharmacokinetics (DMPK) science has significantly advanced the field, leading to improved drug efficacy, safety, and optimization of the drug development process. This discussion explores some of the recent developments in drug discovery and development facilitated by advancements in DMPK science. Predictive ADME Models: Recent developments in DMPK science have led to the creation of robust and predictive models for absorption, distribution, metabolism, and excretion (ADME) properties of drug candidates. These models employ computational techniques, such as machine learning and quantitative structure-activity relationship (QSAR) analysis, to predict a drug candidate’s ADME properties before conducting expensive and time-consuming experiments. Predictive ADME models enable researchers to prioritize drug candidates with favorable pharmacokinetic profiles, resulting in more efficient drug discovery and development processes. In vitro and in vivo DMPK Assays: Advancements in DMPK science have introduced novel in vitro and in vivo assays that provide valuable information on a drug candidate’s metabolism, transport, and clearance. For example, hepatocyte-based in vitro systems can simulate drug metabolism and hepatic clearance, enabling researchers to assess a drug’s potential interactions with metabolic enzymes and transporters. Moreover, microdosing studies using accelerator mass spectrometry (AMS) allow early assessment of a drug candidate’s pharmacokinetics in humans, reducing the risks associated with later-stage clinical trials.

Targeted Drug Delivery: DMPK science has played a crucial role in the development of targeted drug delivery systems. By understanding the drug’s pharmacokinetic properties, researchers can design and optimize drug formulations that improve drug bioavailability, stability, and tissue specificity. For instance, liposomal formulations and nanoparticles can enhance drug solubility, prolong systemic circulation, and selectively deliver drugs to specific tissues or cells. These advancements offer opportunities for personalized medicine and the treatment of diseases that were previously challenging to target effectively.

Drug-Drug Interactions and Safety Assessment: Understanding drug-drug interactions (DDIs) is critical in drug discovery and development to ensure patient safety and avoid adverse drug reactions. Recent developments in DMPK science have led to the identification and characterization of potential DDIs through in vitro and in vivo experiments. Moreover, computational models have been developed to predict and prioritize potential DDIs based on drug metabolism and transport pathways. These advancements help researchers optimize drug combinations and minimize the risk of unexpected drug interactions during clinical trials. Pharmacokinetic Modeling and Simulation: Advancements in DMPK science have facilitated the development of pharmacokinetic modeling and simulation approaches. These techniques utilize mathematical models and computer simulations to predict drug behavior in different populations, such as pediatric, geriatric, and diseased patients. Pharmacokinetic modeling and simulation allow researchers to optimize dosing regimens, predict drug exposure, and assess the impact of factors like genetic variations on drug pharmacokinetics. Consequently, these approaches enhance the efficiency of clinical trials and promote individualized treatment strategies [7-17].

Conclusion

Recent developments in DMPK science have significantly contributed to drug discovery and development, enabling researchers to make informed decisions at various stages of the process. Predictive ADME models, advanced DMPK assays, targeted drug delivery systems, safety assessments, and pharmacokinetic modeling have revolutionized the field. These advancements offer the potential to accelerate the drug development timeline, improve drug efficacy and safety, and ultimately enhance patient outcomes in the future. Continued integration of DMPK science into drug discovery and development processes holds great promise for the development of innovative and effective therapeutic interventions.

1. Maurer (2018) Mass Spectrometry for Research and Application in Therapeutic Drug Monitoring or Clinical and Forensic Toxicology. Ther Drug Monit 40:389-393.

Indexed at, Google Scholar, Crossref

2. Montplaisir J (2003) Zopiclone and zaleplon vs benzodiazepines in the treatment of insomnia: Canadian consensus statement. Hum Psychopharmacol 18:29-38.

Indexed at, Google Scholar, Crossref

3. John FW (2012) Principles and Procedures in Forensic Toxicology. Clin Lab Med 32:493-507.

Indexed at, Google Scholar, Crossref

4. Szeremeta M, Pietrowska K, Niemcunowicz-Janica A, Kretowski A, Ciborowski M (2021)

Indexed at, Google Scholar, Crossref

5. Hans H (2002) Role of Gas Chromatography-Mass Spectrometry With Negative Ion Chemical Ionization in Clinical and Forensic Toxicology, Doping Control, and Biomonitoring. Ther Drug Monit 24:247-254.

Indexed at, Google Scholar, Crossref

6. Marc A LeBeau (2020) ANSI/ASB Standard 036 for Method Validation in Forensic Toxicology Has Replaced SWGTOX’s Version. J Anal Toxicol 44:414.

Indexed at, Google Scholar, Crossref

7. Montplaisir J, Hawa R, Moller H, Morin C, Fortin M, et al. (2003) Zopiclone and zaleplon vs benzodiazepines in the treatment of insomnia: Canadian consensus statement. Hum Psychopharmacol 18:29-38.

Indexed at, Google Scholar, Crossref

8. Stewart R, Besset A, Bebbington P, Brugha T, Lindesay J, et al. (2006) Insomnia comorbidity and impact and hypnotic use by age group in a national survey population aged 16 to 74 years. Sleep 29:1391-1397.

Indexed at, Google Scholar, Crossref

9. Glass J, Lanctot KL, Herrmann N, Sproule BA, Busto UE, et al. (2005) Sedative hypnotics in older people with insomnia: meta-analysis of risks and benefits. BMJ 331:1169.

Indexed at, Google Scholar, Crossref

10. Dolder C, Nelson M, McKinsey J (2007) Use of non-benzodiazepine hypnotics in the elderly: are all agents the same? CNS Drugs 21:389-405.

Indexed at, Google Scholar, Crossref

11. Dang A, Garg A, Rataboli PV (2011) Role of zolpidem in the management of insomnia. CNS Neurosci Ther 17:387-397.

Indexed at, Google Scholar, Crossref

12. Wagner J, Wagner ML (2000) Non-benzodiazepines for the treatment of insomnia. Sleep Med Rev 4:551-581.

Indexed at, Google Scholar, Crossref

13. Dolder CR, Nelson MH (2008) Hypnosedative-induced complex behaviours: incidence, mechanisms and management. CNS Drugs 22(12):1021-1036.

Indexed at, Google Scholar, Crossref

14. Barbera J, Shapiro C (2005) Benefit-risk assessment of zaleplon in the treatment of insomnia. Drug Saf 28:301-318.

Indexed at, Google Scholar, Crossref

15. Verster JC, Veldhuijzen DS, Volkerts ER (2004) Residual effects of sleep medication on driving ability. Sleep Med Rev 8:309-325.

Indexed at, Google Scholar, Crossref

16. Nutt DJ, Stahl SM (2010) Searching for perfect sleep: the continuing evolution of GABAA receptor modulators as hypnotics. J Psychopharmacol 24:1601-1612.

Indexed at, Google Scholar, Crossref

17. Lech G, Slotwinski R, Slodkowski M, Krasnodebski IW (2016) Colorectal cancer tumour markers and biomarkers: Recent therapeutic advances. World J Gastroenterol 22: 1745-1755.

Indexed at, Google Scholar, Crossref