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Review
. 2022 Apr 21;12(5):669.
doi: 10.3390/jpm12050669.

A State-of-the-Art Roadmap for Biomarker-Driven Drug Development in the Era of Personalized Therapies

Victoria Serelli-Lee  1   2 , Kazumi Ito  1   3 , Akira Koibuchi  1   4 , Takahiko Tanigawa  1   5 , Takayo Ueno  1   6 , Nobuko Matsushima  1   7 , Yasuhiko Imai  1   6
Affiliations
Review

A State-of-the-Art Roadmap for Biomarker-Driven Drug Development in the Era of Personalized Therapies

Victoria Serelli-Lee et al. J Pers Med. .

Abstract

Advances in biotechnology have enabled us to assay human tissue and cells to a depth and resolution that was never possible before, redefining what we know as the "biomarker", and how we define a "disease". This comes along with the shift of focus from a "one-drug-fits-all" to a "personalized approach", placing the drug development industry in a highly dynamic landscape, having to navigate such disruptive trends. In response to this, innovative clinical trial designs have been key in realizing biomarker-driven drug development. Regulatory approvals of cancer genome sequencing panels and associated targeted therapies has brought personalized medicines to the clinic. Increasing availability of sophisticated biotechnologies such as next-generation sequencing (NGS) has also led to a massive outflux of real-world genomic data. This review summarizes the current state of biomarker-driven drug development and highlights examples showing the utility and importance of the application of real-world data in the process. We also propose that all stakeholders in drug development should (1) be conscious of and efficiently utilize real-world evidence and (2) re-vamp the way the industry approaches drug development in this era of personalized medicines.

Keywords: Japan; biomarker-driven drug development; clinical trial renovation; data ecosystem; disease blueprint; ecosystem for personalized therapies; genome medicine; personalized medicine; real-world data/evidence.

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Conflict of interest statement

All authors are employees of their organizations listed in the author affiliations section. This work is an effort of the authors’ participation as members on the Japan Pharmaceutical Manufacturers’ Association clinical biomarkers taskforce.

Figures

Figure 1
Figure 1
Personalized therapy ecosystem (PTE). A pictorial representation of a PTE. A biomarker “lifecycle” is broken down into 3 stages—discovery, translation and qualification. Biomarker testing in the clinic generates real-world data/evidence (RWD/E) that feeds back into (supports) all stages of biomarker-driven drug development. Increased efficiency in development leads to more clinically validated biomarkers that can be used in clinical practice.
Figure 2
Figure 2
Roadmap for biomarker-driven drug development for personalized therapies.
See this image and copyright information in PMC

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