Merck will use Protillion Biosciences’ tech to design biologic therapies for therapies across undisclosed indications.
The next stop on biopharma’s AI train is Merck, which is bringing on California’s Protillion Biosciences to combine large-scale data generation and AI design to advance a suite of novel biologic therapies.
Merck is making an undisclosed upfront payment, according to a Tuesday release, as well as offering up to $510 million in R&D and commercial milestones. The companies did not name the specific targets or disease areas they plan on addressing, only saying that they will collaborate on “multiple therapies.”
For its investment, Merck will gain access to Protillion’s Prot-MaP technology, a “megascale data generation platform” that the biotech claims will provide training sets specifically tailored to protein design AI models.
This approach can simultaneously and quantitatively assess protein therapy candidates “at a massive scale” to find those that are likely to be specific to and have high affinity for their intended targets, as well as have “uncompromised manufacturability,” according to Protillion’s website.
Protillion’s tech “offers a compelling opportunity” for Merck’s drug development capabilities, Juan Alvarez, vice president of discovery biologics at Merck Research Laboratories, said in a statement. The platform has the “potential to transform the speed and precision with which we characterize protein landscapes and identify novel therapeutic candidates,” he added.
AI is quickly becoming a central force in biopharma as more and more companies—including the industry giants—integrate the technology into drug development processes. Eli Lilly in particular has been investing heavily in AI. In April, the pharma put up to $2.25 billion on the line to bring on Profluent Bio and its machine learning platform to design therapeutic enzymes for a variety of genetic targets.
Last month, Lilly struck again, along with Bristol Myers Squibb and Incyte, minting respective AI alliances to integrate machine learning models into different parts of their operations, such as data sharing and corporate and commercial functions.
Most recently, Alnylam earlier this month gave $30 million to Inceptive Nucleics, gaining access to a machine learning engine that learns the underlying biology behind diseases. Alnylam, which has earmarked a total of $2 billion for this agreement, will use Inceptive’s approach to optimize its siRNA design and selection.
The AI wave also saw the second largest financing round in biopharma history, with Alphabet’s Isomorphic Labs bringing in $2.1 billion in May, despite having no asset in the clinic yet.
