{"id":76388,"date":"2026-06-17T02:06:09","date_gmt":"2026-06-17T02:06:09","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/76388\/"},"modified":"2026-06-17T02:06:09","modified_gmt":"2026-06-17T02:06:09","slug":"merck-protillion-launch-ai-drug-discovery-collaboration-with-up-to-510m-in-milestone-payments","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/76388\/","title":{"rendered":"Merck, Protillion Launch AI Drug Discovery Collaboration with Up-to-$510M in Milestone Payments"},"content":{"rendered":"

\"\"<\/a>A Merck & Co. researcher at work. Merck will partner with Protillion Biosciences to discover multiple new therapy candidates, through a collaboration that could generate up to $510 million in milestone payments for the artificial intelligence-based drug design company whose \u201clab-in-the-loop\u201d approach combines AI with a continuous feedback loop of experimental wet-lab data. [Merck & Co.]<\/p>\n

Merck & Co. will partner with Protillion Biosciences to discover multiple new therapy candidates through a collaboration that could generate up to $510 million in milestone payments for the artificial intelligence-based drug design company whose \u201clab-in-the-loop\u201d approach combines AI with a continuous feedback loop of experimental wet-lab data.<\/p>\n

The collaboration, launched through a multi-target discovery collaboration and license agreement, is designed to combine Merck\u2019s global expertise in discovering novel therapeutics with Protillion\u2019s Prot-MaP\u2122 on-chip antibody discovery platform.<\/p>\n

Prot-MaP, short for Protein Display on a Massively Parallel Array, is designed to facilitate AI-based optimization of therapeutic antibodies through the quantitative analysis of protein libraries with unprecedented speed, scale, and precision, characterizing millions of variants per run and avoiding the common pitfalls of model overfitting.<\/p>\n

The result, according to Protillion, is the identification of optimized biologics with sophisticated therapeutic profiles such as pH-dependent sweeping and multi-target specificity\u2014profiles that are difficult to achieve with traditional methods.<\/p>\n

Protillion says Prot-MaP is intended to enable the engineering of novel biologics by generating megascale, just-in-time quantitative antibody binding datasets for protein design AI. The platform enables the generation of tens of millions of clusters of immobilized proteins directly on an Illumina DNA sequencing flow cell through efficient tethered in situ transcription and translation.<\/p>\n

Prot-MaP was invented by the company\u2019s CEO and co-founder, Curtis Layton, and co-founder Will Greenleaf, PhD, a professor of genetics at Stanford University School of Medicine and a member of Protillion\u2019s Scientific Advisory Board. After receiving his PhD in computational biology from Duke University, Layton studied with Greenleaf as a postdoctoral fellow in the genetics department at Stanford Medicine.<\/p>\n

\"\"Curtis Layton, PhD, CEO and co-founder of Protillion Biosciences<\/p>\n

Layton developed Prot-MaP while working in Greenleaf\u2019s lab, then organized Protillion in 2019 to commercialize the technology. Layton\u2019s work pioneered a new approach to high-throughput interrogation of biochemical systems, tackling ultra-high-impact technology approaches for drug discovery by uniting fields that included protein engineering, next-generation sequencing technology, molecular biology, in vitro transcription and translation, computational biology, software development, and various engineering disciplines.<\/p>\n

Days rather than months<\/p>\n

\u201cProt-MaP is a technology platform that allows us to test millions of protein interactions simultaneously, generating an unprecedented amount of data in a matter of days rather than months. For example, we can rapidly evaluate large libraries of therapeutic protein candidates to see how they bind to different targets and how they behave under different biological conditions,\u201d Robert Hollingsworth, PhD, Protillion\u2019s CSO, told GEN.<\/p>\n

\u201cWe then combine that data with proprietary AI and machine learning tools to understand what drives the best-performing proteins and quickly design improved candidates. This gives us the ability to engineer antibodies with highly specific characteristics, such as stronger and more precise target binding, the ability to engage multiple targets, or the ability to activate only under certain physiological conditions,\u201d Hollingsworth explained. \u201cIn practical terms, Prot-MaP helps us discover and optimize better drug candidates faster, with a level of insight and precision that has not previously been possible at this scale.\u201d<\/p>\n

Prot-MaP allows Protillion to test up to one million protein variants simultaneously in a single experiment and generate results in as little as 48 hours.<\/p>\n

\u201cBecause we operate multiple proprietary platforms in parallel, we can rapidly scale that capability and generate enormous amounts of experimental data on demand,\u201d Hollingsworth explained.<\/p>\n

What makes Prot-MaP unique, he continued, is not just its scale, but its combination of scale, speed, and AI.<\/p>\n

\"\"Robert Hollingsworth, PhD, Protillion Biosciences\u2019 CSO<\/p>\n

\u201cThe platform is designed to seamlessly connect high-throughput protein testing with proprietary machine learning models, allowing us to quickly identify promising drug candidates, understand what makes them work, and design improved versions,\u201d Hollingsworth said. \u201cThis enables us to tackle everything from discovering entirely new therapeutic molecules to optimizing existing candidates for multiple desired characteristics. In practical terms, Prot-MaP helps us find and develop better biologic medicines faster and more efficiently than traditional approaches.<\/p>\n

Opposite approach<\/p>\n

How does Prot-MaP overcome the complexity of protein molecules, which has long been a hurdle in protein and biologics design?<\/p>\n

\u201cMany companies start with AI and then look for data. We took the opposite approach,\u201d Hollingsworth said.<\/p>\n

Rather than relying primarily on computer predictions of protein structure, he elaborated, Protillion can apply Prot-MaP to directly generate large-scale functional data and identify the best therapeutic candidates based on real-world experimental results.<\/p>\n

\u201cWhat makes this especially powerful is the sheer scale of the data we can generate. While much of the industry has focused on applying AI to relatively limited biological datasets, we believe that the biggest challenge in drug discovery is obtaining enough high-quality data to truly understand the complexity of protein function. Prot-MaP was built to solve that problem,\u201d Hollingsworth said.<\/p>\n

By generating millions of protein measurements in parallel, Protillion says, it can create the kind of rich, large-scale datasets needed to train more powerful and predictive machine learning models. Those models, in turn, help design and optimize better therapeutic candidates faster and with greater precision.<\/p>\n

\u201cProt-MaP combines high-throughput experimentation with AI. The platform allows us to rapidly generate the data, and the AI helps us learn from it\u2014creating a cycle that accelerates the discovery of next-generation biologic medicines,\u201d Hollingsworth said.<\/p>\n

Speaking with GEN, Layton said Protillion and Merck have charted a course for the start of their drug discovery collaboration.<\/p>\n

\u201cOur first two programs focus on inflammatory diseases, where we see significant unmet medical need and strong opportunities for differentiation,\u201d he said.<\/p>\n

Immune-mediated inflammatory disorders<\/a> are Merck\u2019s specialty within its therapeutic area of focus in immunology. Merck focuses on several other therapeutic areas<\/a>, which include oncology, vaccines, infectious diseases, cardiometabolic and respiratory diseases, neuroscience, and ophthalmology.<\/p>\n

\u201cHowever, the Prot-MaP platform\u2019s capabilities extend far beyond inflammation, enabling the discovery and development of novel biologics across a broad range of therapeutic areas,\u201d Layton added. \u201cAs we continue to advance the platform, we expect to expand into additional disease areas where its unique capabilities can have the greatest impact.\u201d<\/p>\n

Tech-focused pipeline collaborations <\/p>\n

Merck has launched several tech-focused pipeline collaborations in recent months aimed at replenishing its cancer and immunology pipelines, with the goal of developing new therapies that can recoup the billions of dollars in sales the pharma giant will lose as patent exclusivity expires<\/a> in the United States and elsewhere for its aging blockbusters, including cancer immunotherapy Keytruda\u00ae (pembrolizumab) and Gardasil\u00ae 9 (Human Papillomavirus 9-valent Vaccine, Recombinant).<\/p>\n

In March, Merck inked an up-to-$2.2 billion collaboration with Quotient Therapeutics<\/a>\u00a0to apply Quotient\u2019s somatic genomics platform\u00a0to discover novel drug targets in inflammatory bowel disease (IBD). Also that month, Merck launched a partnership with Infinimmune to apply its\u00a0Anthrobody\u00ae\u00a0discovery platform and GLIMPSE\u2122 antibody language model to identify and develop antibody candidates against multiple undisclosed Merck-designated targets. Merck agreed to pay Infinimmune an undisclosed upfront payment and up to $838 million in milestone payments.<\/p>\n

Merck has also launched several tech-focused partnerships, with partners that include:<\/p>\n

Google Cloud\u2014An up-to-$1 billion collaboration announced in April to deploy an agentic platform across Merck\u2019s R&D, manufacturing, commercial, and corporate functions. Google Cloud engineers are working alongside Merck teams to deploy Google Cloud\u2019s most sophisticated AI, including Gemini Enterprise.
\nTempus AI\u2014An expanded, multi-year collaboration of undisclosed value announced in March, aimed at accelerating discovery and development of precision medicine biomarkers, and supporting Merck\u2019s oncology and potentially broader therapeutic portfolios.
\nMayo Clinic\u2014An R&D agreement of undisclosed value to apply AI, advanced analytics, and multimodal clinical data to support drug discovery and development. The agreement integrates Mayo Clinic\u2019s Platform architecture, as well as clinical and genomic datasets, with Merck\u2019s ambition of harnessing AI-enabled virtual cell technologies to enhance disease understanding, improve target identification, and drive early development decisions.<\/p>\n

In its latest collaboration, Merck has agreed to pay Protillion an undisclosed upfront payment, plus up to $510 million in payments tied to achieving research, development, and commercial milestones toward the successful development of an unspecified number of therapies.<\/p>\n

\u201cCompelling opportunity\u201d<\/p>\n

\u201cPowerful emerging technologies offer the potential to transform the speed and precision with which we characterize protein landscapes and identify novel therapeutic candidates,\u201d Juan Alvarez, PhD, vice president, discovery biologics at Merck Research Laboratories, said in a statement. \u201cProtillion\u2019s platform offers a compelling opportunity, and we look forward to working with the team to advance these programs.\u201d<\/p>\n

Illumina\u2019s venture capital arm, Illumina Ventures, is among investors in Protillion, having joined ARCH Venture Partners in 2022 to co-lead an $18 million financing in 2022.<\/p>\n

Based in Carlsbad, CA, Protillion has grown rapidly to a workforce of 30 people. In March, Protillion hired Robert Hollingsworth, PhD, a drug development executive with more than 30 years\u2019 experience in biopharma, as CSO through a placement by executive search firm CollectiveMinds. Before joining Protillion, Hollingsworth was CSO at Shoreline Therapeutics, and earlier held positions in companies that included Pfizer (as vp and CSO of cancer vaccines and immunotherapeutics), Pharmacia & Upjohn (since absorbed into Pfizer), GlaxoSmithKline (GSK), and MedImmune (acquired by AstraZeneca).<\/p>\n

Protillion says it is continuing to expand its team and facilities, with the aim of supporting its internal pipeline and high-value strategic partnerships.<\/p>\n

\u201cWe plan to hire six more FTEs [full-time equivalents] by the end of the year,\u201d Layton said.<\/p>\n","protected":false},"excerpt":{"rendered":"A Merck & Co. researcher at work. Merck will partner with Protillion Biosciences to discover multiple new therapy…\n","protected":false},"author":2,"featured_media":76389,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[24,41827,41821,41822,41831,25,23236,41823,14372,41824,1941,41825,41836,27670,37450,41832,132,10121,41833,7335,9965,41654,41826,10123,10125,359,41834,9749,10126,41835,66,41828,19731,4359,4082,41829,41830,6873,28347],"class_list":["post-76388","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","tag-ai","tag-and-therapeutics","tag-anti-inflammatory-drugs","tag-antibodies-immune-system","tag-arch-venture-partners","tag-artificial-intelligence","tag-astrazeneca","tag-biomolecules","tag-diagnosis","tag-dna-sequencing-sequencing","tag-drug-discovery","tag-drug-research-and-development","tag-gardasil","tag-gen-edge","tag-genetic-engineering-and-biotechnology","tag-glaxosmithkline","tag-google","tag-illumina","tag-illumina-ventures","tag-immunology","tag-industry-news","tag-infinimmune","tag-inflammation","tag-keytruda","tag-mayo-clinic","tag-medicine","tag-medimmune","tag-merck","tag-merck-co","tag-merck-research-laboratories","tag-news","tag-next-generation-sequencing-sequencing","tag-pfizer","tag-protein-engineering","tag-proteins","tag-sequencing","tag-technology-and-computational-biology","tag-tempus","tag-therapeutics"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/76388","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=76388"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/76388\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/76389"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=76388"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=76388"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=76388"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}