There’s no easy answer to
the fundamental question in drug development “Is this going to work?”

Bringing a drug to market can cost up to $2B, yet clinical trials yield a 90% failure rate. Why? Current tools and assays can’t accurately predict how a drug will act once it enters a patient’s body. 

Even when drugs receive FDA approval, adverse drug reactions are the fourth leading cause of death in America. On top of that, up to 60% of prescribed medications are ineffective.

Syntensor helps drug developers address both these challenges. They’re building models designed to better predict toxicity or lack of efficacy, the key causes of clinical trial failure, before the trials start.

Improving the efficacy and safety of new medications could save companies billions of dollars in R&D costs. It could also save lives.

Combining the power of
AI-driven models and computer-aided design (CAD) for biology.

Syntensor has developed a cutting-edge platform to improve drug development by simulating how drugs interact with the body at a cellular and tissue level. By modeling complex mechanistic interactions through cutting-edge AI, Syntensor can predict how effective a drug will be and identify potential side effects before clinical trials begin.

The added computational power and machine learning capabilities enable Syntensor to work towards a true platform simulator for biology (much as is done with software like Cadence for semiconductor development and Autodesk for CAD).

The goal is a platform that is generalizable across diseases, therapeutic modalities, and patient genotype and phenotype. 

The company’s advanced simulation tools hold the potential to reduce failure rates, expedite the drug discovery process, and save significant costs.

Physicians and scientists will benefit from being able to explore the effects of drugs on the body much earlier than with current techniques.

A Successful Validation Project and Collaborations with Leading Institutions 

Syntensor raised seed round funding from Lifeforce Capital, Morningside Ventures, PTK Capital, Hula and had subsequent funding form Lexi Ventures. They’ve completed one validation project and are currently entering a pilot phase with multiple firms with ~$50B in AUM. 

Collaborations (such as HyenaDNA) with prestigious institutions like HAI at Stanford and MILA, involving renowned experts in AI and bioinformatics show Syntensor’s research capabilities.

Write Software Once,
Deploy Many Times

That’s the key principle of the SaaS business model where companies pay on a monthly or annual basis to use the software.

Syntensor initially plans to reinvest recurring revenue into R&D, following a model that has led to high growth rates (40%+ CAGR) for enabling tooling providers in other industries. Their approach aims to replicate the success of companies like Cadence Design Systems by applying it to the biotech market.

As Syntensor's technology becomes more accurate, they can enter different markets. Initially, Syntensor is targeting biotech investors (hedge funds, venture capitalists) who benefit directly from funded companies being able to better predict drug success and can act quickly. 

A Foundation model
for Biology with a SaaS business approach

Syntensor aims to revolutionize drug development by creating advanced simulation tools akin to the “CAD for biology.” Their goal is to drastically reduce high failure rates in clinical trials and mitigate adverse drug reactions.

They are also working to make their simulator generalizable across applications, creating a foundation model for biology and opening the door to a SaaS-like business model.

Syntensor’s team includes industry veterans and experts from DeepMind, Novartis, GSK, and Stanford. Their collective experience in AI, bioinformatics, and drug discovery strengthens the company's ability to innovate and execute its vision.