Biomarkers and a Blockbuster Drug
The Surprising Story Behind
Merck’s Keytruda
June 1, 2021
(this post is also featured on the Bridge Informatics blog)
The success of Merck’s Keytruda (pembrolizumab) seems like a pharma fairy tale. Highly effective in treating advanced solid tumors and bringing in $43 billion in 2020 sales for Merck, Keytruda is also the first cancer drug to receive the FDA’s breakthrough therapy designation.
It then comes as a surprise to learn that the drug was almost shelved. What follows is a story to vindicate the development of companion diagnostics, for it was the use of biomarkers that ultimately brought Keytruda’s potential to fruition.
Keytruda is a humanized monoclonal antibody that harnesses the immune system to kill tumor cells by blocking PD-1, a T-cell inhibitor. The drug was borne out of a PD-1 immuno-oncology research program at Organon (a company acquired by Schering Plough in 2007, which itself was acquired by Merck in 2009).
Keytruda’s progression from a low-ranking oncology research program on PD-1, barely surviving two acquisitions, to an exemplar for companion diagnostics in drug development was sparked by competition from pharma company Bristol Myers Squibb (BMS).
In mid-2010, BMS’ PD-1-targeting drug Opdivo (nivolumab) was showing potential, and they had also just published a successful clinical trial of a drug targeting a related T-cell inhibitor molecule in melanoma patients, CTLA4.
BMS’ successes lit a fire under Merck’s R&D team, and they rebooted the Keytruda program, testing its efficacy in a phase I trial with remarkable results in advanced melanoma patients.
This was the turning point in Keytruda’s development. Merck researchers (fearing they were years behind BMS) turned to biomarkers to yield the most convincing clinical trial results possible and get Keytruda approved.
PD-1’s natural ligand, PD-L1, was the strongest candidate for a biomarker to identify tumors that would respond well to a PD-1 inhibitor like Keytruda. First used for melanoma, selection was then expanded to non-small-cell lung carcinoma (NSCLC).
NSCLC patients now have an FDA-approved, PD-L1 companion diagnostic for treatment with Keytruda.
Remarkably, a further biomarker for Keytruda treatment was identified: a signature of the failure to correctly repair mismatched DNA called MSI-High. The remarkable effectiveness of Keytruda against MSI-High tumors led to the FDA’s first approval of a cancer drug based on a genetic signature alone, regardless of the tumor’s location in the body.
The story of Keytruda’s development sheds light on the potential of companion diagnostics, and the data analysis teams needed to develop them. Biomarker identification relies on bioinformatics: analyzing the -omics data to identify biological signatures for the next blockbuster drug target.
Dan Ryder, CEO and Managing Director, Bridge Informatics
Dan is the founder of Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, he can be contacted at dan.ryder@bridgeinformatics.com.
Sources:
https://www.forbes.com/sites/davidshaywitz/2017/07/26/the-startling-history-behind-mercks- new-cancer-blockbuster/?sh=4739034d948d https://www.nytimes.com/2017/06/08/health/cancer-drug-keytruda-tumors.html?_r=0 https://science.sciencemag.org/content/357/6349/409 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5452070/ https://www.agilent.com/cs/library/brochures/29147_pd-l1-ihc-22c3-nsclc-1-percent- brochure-eu.pdf https://s21.q4cdn.com/488056881/files/doc_financials/2020/q4/4df43d8f-8b85-45da-92ef- 7ad82f343c3b.pdf
