Insitro is an operator of a data-driven drug discovery and development company that utilizes machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients. The company uses state-of-the-art technologies from bioengineering enabling it to generate high-throughput, functional genomic data sets and aligning them with patient data via novel machine learning methods, thereby building predictive models that can accelerate target selection and the design and development of effective therapeutics. In 2018, Daphne Koller established Insitro in South San Francisco, California..
Insitro is an operator of a data-driven drug discovery and development company that utilizes machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients. The company uses state-of-the-art technologies from bioengineering enabling it to generate high-throughput, functional genomic data sets and aligning them with patient data via novel machine learning methods, thereby building predictive models that can accelerate target selection and the design and development of effective therapeutics. In 2018, Daphne Koller established Insitro in South San Francisco, California..
Focus: Machine-learning-driven drug discovery using high-throughput biology
Total disclosed funding: $643M (through 2021)
Company Overview
Problem Domain
Drug discovery and development; identifying targets and designing therapeutics using ML and high-throughput biology.
Founded
2018
Industry
Biotechnology / Drug discovery
Tech Stack
Machine learning
High-throughput biology
Human genetics / genomic data
Predictive modeling
Funding Track Record
Series C- 2021-03-15
$400,000,000
Series C announced March 15, 2021; participation from multiple existing and new investors.
Series A- 2019
$100,000,000
Reported Series A announced in 2019.
Investor Signal
“Mix of life-science VCs, technology investors, and large institutional asset managers (including CPP Investments, Andreessen Horowitz, GV, Two Sigma, T. Rowe Price, BlackRock, ARCH Venture Partners, Third Rock Ventures, Foresite Capital, Casdin, Temasek, SoftBank Investment Advisors, Alexandria Venture Investments, HOF Capital).”
Founders
What we do
Join the Team
Scientist II/Senior Scientist, DEL Chemistry
On-SiteSan Francisco Bay Area, US
On-Site • San Francisco Bay Area, US
The Opportunity
insitro uses advanced machine learning to analyze extensive biological and clinical data, aiming to improve the success rate of drug discovery and development. One of insitro's key platforms for generating small molecule therapeutics in neurological and metabolic diseases integrates DNA-encoded libraries (DEL) with machine learning. We are seeking a creative and data-oriented DEL synthetic chemist to lead lab-based DEL synthesis (on- and off- DNA) and data analysis. This role will play a key part in the application of machine learning to enhance the effectiveness and speed of our preclinical drug development programs. This position's reporting structure will be dependent on your specific skillset and will require you to be in our South San Francisco headquarters
five days per week.Responsibilities
Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.
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Design, develop, and validate DEL synthesis schemes with high structural diversity using robust chemistries that complement our machine learning platform
Develop, validate, and implement innovative on-DNA chemistry strategies while providing technical expertise in synthetic methods
Collaborate with our Medicinal Chemistry and Machine Learning teams to enhance DEL library portfolio, hit expansion strategies, and hit confirmation activities
Interface with selections team in designing DEL selections to various protein classes
Contribute to the analysis of DEL data and aid guidance of computational tool design and methodologies that strengthen DEL data analysis
Support hit generation activities across therapeutic areas
Perform the synthesis of DNA-Encoded libraries and hits (on-DNA) internally and oversee synthetic chemistry through external partners (off-DNA)
Lead cross-functional teams in drug discovery campaigns, bringing together experimental and computational expertise
Drive the implementation of machine learning approaches in DEL design, screening, and analysis
About You
Education and Experience
PhD in, Medicinal Chemistry, Chemical Biology, Computational Chemistry or related discipline with 4+ years of relevant experience
MS with 8+ years or BS with 10+ years of relevant experience will also be considered
Technical Expertise
Exposure to, knowledge of, and preferably hands-on experience, across aspects of DNA-encoded Library technology, including:
Library design and synthesis strategy
DEL selection methodologies and optimization
Next Generation Sequencing (NGS) data handling
Advanced DEL data analysis and interpretation
Hit confirmation and validation strategies
Proficiency with modern cheminformatics platforms, computational chemistry tools, and structure-based design approaches
Experience in data visualization, statistical analysis, and interpretation of large chemical datasets
Interest in integrating machine learning concepts with traditional DEL methodologies
Scientific Accomplishments
Demonstrated scientific impact through publications, patents, or successful drug discovery programs ideally leveraging DEL technology against diverse targets
Proven contributions to hit generation, hit-to-lead or lead optimization campaigns
Leadership and Collaboration
Demonstrated leadership in driving scientific projects and mentoring junior scientists
Successful track record of cross-functional collaboration with computational, biological, and chemical teams
Experience working effectively with CROs and external partners
History of professional engagement that advances both organizational goals and the broader scientific field
Core Competencies
Exceptional analytical thinking and creative problem-solving abilities
Strong organizational skills with ability to manage multiple priorities in a fast-paced environment
Outstanding communication skills to effectively translate complex scientific concepts across disciplines
Ability to thrive at the intersection of experimental chemistry and computational approaches
Enthusiasm for working in a data-driven, machine learning-focused drug discovery environment
Compensation & Benefits At Insitro
Our target starting salary for successful US-based applicants for this role is $135,000 - $180,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.
This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.
In addition, insitro also provides our employees:
401(k) plan with employer matching for contributions
Excellent medical, dental, and vision coverage as well as mental health and well-being support
Open, flexible vacation policy
Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)
Quarterly budget for books and online courses for self-development
Support to attend professional conferences that are meaningful to your career growth and role's responsibilities
New hire stipend for home office setup
Monthly cell phone & internet stipend
Access to free onsite baristas and cafe with daily lunch and breakfast for employees who are either onsite or hybrid
Access to free onsite fitness center for employees who are either onsite or hybrid
Access to a free commuter bus and ferry network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area
insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process.
About Insitro
insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com.
