By Mohamed Hassanein (Pfizer), Xiazi Qiu (Novartis), Jianing Zeng (Bristol Myers Squibb), and Amanda Hays (BioAgilytix)
Biomarkers in Drug Development
Biomarkers are objective and measurable indicators of biological conditions such as disease state, physiological function, exposure to environmental factors, or response to therapeutic interventions (1). Biomarkers can be genetic, multi-analyte “omics”, digital, morphological, or behavioral(1-7).
Biomarkers can inform decisions at various stages of drug development, such as target identification, lead optimization, preclinical studies, clinical trials, and regulatory approval.
Biomarkers can help to identify patients who are likely to respond to a specific treatment or those who may experience adverse events. Most importantly, biomarkers can be used to monitor the response to drugs and provide early indications of their efficacy. Biomarkers are routinely used for determining the optimal dose of a drug for a particular patient or population and can identify potential safety issues early in the drug development process. Furthermore, biomarkers can support the regulatory approval of a drug by providing evidence of its efficacy or safety. However, drug development is a complex process that involves many other factors beyond biomarkers such as pharmacokinetics, toxicology, clinical trial design, and manufacturing (8). Therefore, biomarkers can serve as a valuable tool to guide the entirety of the drug development process when used in tandem with toxicological, clinical, and pharmacological readouts.
The “Context of Use” Concept
Due to the diverse applications of biomarker data throughout drug development, validation of bioanalytical methods for biomarker quantitation cannot be simplified to a one-size-fits-all approach and current general bioanalytical method validation guidance may not be suitable for biomarker assay validation (9). Therefore, fit-for-purpose validation is used for biomarker bioanalysis. The purpose is defined early in the method development process by a “Context of Use” (COU) statement. A COU statement would describe the intended uses of the biomarker and its bioanalytical methods, and would govern the acceptable rigor, sensitivity, robustness, precision, and selectivity of the analytical validation (1,9). Based on the COU statement, a specific validation plan including assay validation acceptance criteria can be tailored to the biomarker of interest and its intended use in a specific stage of a program. The COU concept allows customized assay validations for biomarker assays at various stages while maintaining reliable quantitation to support conclusions.
Precision Medicine and the Future of Biomarkers
Biomarkers are driving a paradigm shift toward a precision medicine approach to drug development. By identifying specific molecular or genetic characteristics of a disease or patient population, biomarkers can enable the development of more focused clinical trials, with a greater likelihood of success. Development of such customized therapies can lead to more personalized treatment approaches and potentially better outcomes with fewer side effects. Multi-omics approaches, digital biomarkers, AI and machine learning, real world data (RWD) and patient-centricity are some of the latest trends in biomarkers that are poised to further advance the paradigm shift towards precision medicine in drug development. These technological and computational advances will usher in a new era of personalized and effective treatments, with the potential to transform how we diagnose, treat, and prevent diseases.
A Resource for All: Introduction to Biomarkers e-Course
Given that biomarkers play such a critical role in driving precision medicine and drug development forward, it is important to understand how to accurately detect and measure these analytes. Biomarker quantification comes with its own challenges. There is a wide array of technology platforms that can be used to quantify biomarkers, each with its own subtleties. Since biomarkers can be a critical component of drug development, their analysis can encompass efforts from a variety of stakeholders including but not limited to bioanalytical scientists, clinical pharmacologists, and medical advisors. With these challenges and nuances in mind and in an effort to consolidate information for entry level biomarker scientists, the AAPS Biomarkers and Precision Medicine organized and released the “Intro to Biomarkers: Assay Validation/Qualification, Regulatory Guidance and Application” e-course. The e-course is made up of five modules including lectures on how biomarkers and translational research play an important role in the drug development process, understanding challenges and opportunities for biomarker translation in precision medicine, introduction of the concept of COU (context of use) and how clinical utility drives parameters behind analytical validation. In addition, the e-course highlights considerations for developing and validating LC-MS or LBA biomarker assays including understanding translational biomarker strategy, matrix selection, pre-analytical variables, parallelism, endogenous QCs, ISR, critical reagent considerations, implementation of commercials kits, and multiplexed assays. The e-course is available and free to all AAPS members as a valuable educational resource.
In addition to the e-course as a resource, The AAPS NBC (National Biotech Conference) will feature a Hot Topic session that will take place on April 25th. This hot topic session will be an open forum for questions and discussion with a panel of biomarker and regulatory experts.
In conclusion, biomarkers are a very critical aspect of drug development. It is important to understand why and how they are measured as they have an infinite influence on driving the development of getting lifesaving therapeutics to market.
References
1. Group F-NBW. BEST (Biomarkers, EndpointS, and other Tools) Resource 2016.
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3. Mahadevan N, Christakis Y, Di J, Bruno J, Zhang Y, Dorsey ER, et al. Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices. NPJ Digit Med. 2021;4(1):42.
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7. Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, Granton P, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441-6.
8. Karczewski KJ, Daneshjou R, Altman RB. Chapter 7: Pharmacogenomics. PLoS Comput Biol. 2012;8(12):e1002817.
9. Steven P. Piccoli JMS. Points to Consider Document:Scientific and Regulatory Considerations for the Analytical Validation of Assays Used in the Qualification of Biomarkers in Biological Matrices. Critical Path Institute (C-Path). 2019.