insitro
Drug Discovery & Development
Insitro is a data-driven drug discovery company leveraging machine learning and high-throughput biology to create AI therapeutics.
About insitro
insitro uses machine learning and data at scale to decode the complexities of biology and unlock transformative new medicines.
Leadership Team
Key executives and founders sourced from public LinkedIn profiles.
For most of my career, I've been working at the boundary of two disciplines: machine learning and biomedicine. But until recently, machine learning has not had the same impact on biomedicine as it's had on so many other challenging domains. The reason for that is twofold: not enough high-quality, relevant data; and not enough "bilingual" people who understand both domains and are able to identify the important problems and design the "right" solutions. At insitro, we aim to address both these challenges, and help address an important societal problem: design novel, safe, and effective therapies that help more people, faster, and at a lower cost. We have many exciting and challenging problems, and are building a diverse team of exceptionally talented people. Please join us!
- Full-stack and customer-focused. - 2 years as Lead Software Engineer at Culture Biosciences building their Console platform to solve the logistics of migrating in-house bio experimentation to Culture's lab-in-the-cloud. - 2 years CTO at Presscast.io, a seed-funded SaaS marketplace seeking to improve how people get paid for content on the web. - 10+ years professional experience developing data-driven web and desktop applications in C/C++, C#, Python, Go, and Javascript (NodeJS).
• Medical geneticist & industry scientist dedicated to leverage genetics & AI for improving human health • Scientific focus on how to move insights from human population research towards function & treatments • Pioneering leader & manager of large interdisciplinary R&D teams & complex international projects • Strong interdisciplinary research & medical background in academia, biotech & pharma in EU & US
Senior executive and leader in Biostatistics and Data Science pioneering ML algorithm development, large-scale clinical trial innovations, and strategic initiatives in pharma and diagnostics industries. Key driver in developing market-leading products: from research, ML algorithm discovery, to non-clinical verification and phase 3 clinical validation, US/EU regulatory submissions, and reimbursement. Expertise in executing complicated data science and statistical strategies that drive rapid business growth. Recognized for building high-performing teams and leading strategic and technical execution across portfolios, including cutting-edge clinical trial design, real-world evidence (RWE) generation, and complex modeling to assess clinical utility and shorten study duration. Strategic thinker, clinical trial designer, RWE expert, methodology innovator, and published senior author in reputable journals with 15+ patents internationally.
Mission & Approach
Mission
“At insitro, we are building a different kind of drug company to bring better drugs faster to the patients who can benefit most. Through the power of machine learning (ML) and data at scale, we decode the complexities of biology to unlock transformative new medicines.”
AI Approach
Machine learning, generative AI, self-supervised deep learning, predictive analytics for phenotypic disease modeling and drug discovery
Founding Story
Founded by Daphne Koller (CEO & Founder) who set out to create a unique culture that unites individuals from diverse backgrounds in a single team, bringing together life scientists, data scientists, engineers, and drug hunters.
Products & Solutions
Virtual Human Platform
platformAI-driven platform for identifying key biological drivers and disease-modifying targets
insitro's Virtual Human platform uses AI to identify key biological drivers of disease and discover therapeutic targets. The platform has been used to nominate new targets for ALS treatment and other therapeutic areas, focusing on delivering disease-modifying interventions.
POSH Platform
platformPooled CRISPR screening platform with self-supervised deep learning for gene function inference
insitro's POSH platform integrates pooled CRISPR screening and self-supervised deep learning to break the historic compromise between scale and depth in drug discovery. The platform enables de novo inference of gene function and more rapidly identifies therapeutic targets, validated in Nature Communications.
ChemML
platformAI platform for small molecule drug discovery integrating proprietary binding and functional assays
insitro's ChemML platform integrates proprietary binding and functional assays to discover molecules with potential as next-generation therapies. The platform is being leveraged in collaborations to discover small molecule drugs for conditions like ALS and metabolic diseases.
insitro ML-driven Platform
FlagshipplatformAI/ML platform integrating cellular and clinical data to redefine disease and accelerate drug discovery
insitro's machine learning-driven platform integrates multi-modal phenotypic cellular data produced in automated laboratories with human clinical data to help redefine disease. The platform uses machine learning and generative AI to build and interrogate phenotypic models of disease state, leveraging human genetics to identify causal intervention points and turn them into effective therapeutic interventions in the right patients.
TherML
FlagshipplatformFull stack, modality-agnostic AI platform for drug discovery and design across all major drug modalities
TherML integrates advanced biologics expertise with insitro's existing small molecule and oligonucleotide capabilities, unifying therapeutic design across all major drug modalities in a single AI engine. The platform rapidly engineers the right therapeutic for the right target, addressing the misalignment between biological targets and therapeutic interventions that drives clinical attrition.
Customer Success Stories
Eli Lilly and Company
pharma
Building first-in-kind machine learning models to advance small molecule drug discovery for metabolic diseases
INSIGHT at Moorfields Eye Hospital
hospital
Collaboration to expand research efforts in neurodegeneration using world's largest bioresource of eye images
Bristol Myers Squibb
pharma
Discovery of novel ALS targets and small molecule therapeutics using insitro's AI platforms
Hiring Activity
View Open Roles →Notable roles:
Product & Market
Product Stage
growthPrimary Market
pharmaCompany Details
- Founded
- 2018
- Headquarters
- South San Francisco, CA, USA
- Employees
- 350
- Stage
- series c
- Profile last updated
- June 22, 2026
Category
Drug Discovery & DevelopmentOfficial Sources
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View Profile →Latest Updates
insitro to Acquire CombinAbleAI to Complete its Full Stack, Modality-Agnostic AI Platform for Drug Discovery and Design
TherML integrates CombinAbleAI’s advanced, next generation biologics expertise with insitro’s existing small molecule and oligonucleotide capabilities, unifying therapeutic design across all major drug modalities in a single AI engine SOUTH SAN FRANCISCO, Calif. – Jan. 12, 2026 – insitro, the AI therapeutics company built on causal biology, today announced the acquisition of CombinAbleAI and the launch of insitro’s TherML (Therapeutic Machine Learning) platform. The acquisition, which is expecte
Introducing insitro’s TherML™: Rapidly engineering the right therapeutic for the right target
The primary driver of clinical attrition in drug discovery is often not insufficient scientific rigor, it is misalignment between the biological target and the therapeutic intervention. Discovery organizations have historically structured themselves around technological capabilities, operating as either small molecule, biologics, or oligonucleotide specialists. This specialization creates an underappreciated constraint: modality selection becomes influenced by internal capabilities rather than t
insitro and Bristol Myers Squibb Collaboration Expanded with Nomination of New Targets
Collaboration expands to include two additional therapeutic targets for the treatment of ALS discovered via insitro’s AI-driven Virtual Human platform Joint effort focuses on identifying key biological drivers to deliver disease-modifying interventions for ALS patients SOUTH SAN FRANCISCO, Calif. – – insitro, the AI therapeutics company built on causal biology, today announced the expansion of its strategic collaboration with Bristol Myers Squibb (NYSE: BMY) to advance a broadened portfolio of t
Rewriting the Playbook for ALS Drug Development
Amyotrophic Lateral Sclerosis (ALS) presents one of the most formidable challenges in medical science. For too long, the search for effective treatments has been hampered by a temptation to revisit familiar hypotheses and established biological pathways. While understandable given the slow progress and frequent setbacks, this approach rarely advances the science. At the heart of insitro’s collaboration with Bristol Myers Squibb (BMS) is the deliberate decision to boldly seek novel biology. We ge
insitro Validates AI-Enabled POSH Platform in Nature Communications, Bridging Critical Gap in Drug Discovery
New publication demonstrates that insitro’s POSH platform — integrating pooled CRISPR screening and self-supervised deep learning — successfully breaks the historic compromise between scale and depth to more rapidly identify novel therapeutic targets . SOUTH SAN FRANCISCO, Calif. — Dec. 16, 2025 — insitro, the AI therapeutics company built on causal biology, today announced the publication of research in Nature Communications validating its POSH (Pooled Optical Screening in Human cells) platform
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