Director of Nonclinical Safety, Cambridge, MA

Isomorphic Labs was launched in 2021 to advance human health by building on and beyond the Nobel prize-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. 

Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drug candidates will perform in the clinic and develop medicines to treat and cure some of the world’s most devastating diseases. 

At IsoLabs, we are committed to leveraging state-of-the-art AI to advance precision medicine paradigms and establish new benchmarks for both efficacy and safety by consistently delivering the optimal treatments to the appropriate patients at precisely the right time, which we expect to significantly enhance our overall probability of success. 

Since our founding, we have grown a world-class interdisciplinary team led by founder and CEO Sir Demis Hassabis and President Max Jaderberg. We have built strategic drug discovery collaborations with partners including Eli Lilly, Novartis and Johnson & Johnson, with the Novartis collaboration expanding in February 2025 to double its original scope. Our internal drug candidate pipeline consists of multiple programs across oncology and immunology. 

In March 2025, IsoLabs raised $600 million in its first external funding round, led by Thrive Capital with participation from GV and Alphabet. In May 2026, IsoLabs raised $2.1 billion in a Series B financing round. This investment will power our world-leading AI drug design engine, scale our business globally and progress our drug candidate pipeline. The round was led by Thrive Capital, and includes participation from existing backers Alphabet and GV alongside new investors MGX, Temasek, CapitalG, and the UK Sovereign AI Fund, significantly expanding our global capital base.Isomorphic Labs is scaling globally, with headquarters in London and offices in Lausanne, Switzerland and a US base in Cambridge, Massachusetts. We continue to progress our internal candidate programs towards the clinic while advancing across a broad range of modalities including small molecules, molecular glues, peptides, and antibodies.

We are seeking a highly motivated and experienced Director of Nonclinical Safety to build our nonclinical safety function supporting programs in the Early Development phase.

Reporting directly to the Head of Early Development, you will serve as a key member of the Early Development team. In this critical role, you will be primarily responsible for defining and executing phase-appropriate nonclinical safety strategies as well as pioneering the integration of artificial intelligence in support of oncology and non-oncology programs.

Functional Leadership & Capability Building

• Lead, build, and scale the Nonclinical Safety function within an AI-first drug development environment.
• Serve as the primary internal expert for post-IND nonclinical safety ensuring quality, consistency, and scalability as compounds transition into clinical trials.
• Establish a critical data feedback loop: ensure high-quality data are fed back to computational teams to continuously train, validate, and refine our predictive nonclinical safety AI models.

Portfolio & Program Strategy

• Define and drive nonclinical safety and other translational strategies primarily for small molecule drug candidates in the Early Development phase across oncology and non-oncology indications.
• Execute seamlessly on post-IND (NDA/MAA-enabling) nonclinical toxicology work, including chronic, reproductive, and carcinogenicity studies as needed.
• Establish translational strategies by integrating exploratory nonclinical safety biomarkers and exposure-based modeling plans to predict and de-risk potential effects in humans.
• Integrate in silico safety predictions (e.g., off-target liabilities, digital pathology, predictive DILI models) with traditional data to help build robust, AI-augmented nonclinical safety profiles for compounds in development.
• Collaborate closely with colleagues in Preclinical Development, Clinical Pharmacology, Regulatory Affairs, Quality, and Pharmaceutical Sciences & Manufacturing to ensure the seamless development of drug candidates.

External Partnerships & Regulatory

• Leverage network of global CRO’s and consultants, ensuring data quality, timelines, and cost efficiency in a fast-paced environment.
• Lead nonclinical regulatory strategy and contribute to corresponding documentation, including INDs, IBs, DSURs, briefing books, and NDA/MAA modules (including USPI/labels).
• Represent Isomorphic Labs in regulatory interactions and global health authority meetings (FDA, EMA) as appropriate, leveraging cutting-edge AI and LLM tools to accelerate document drafting, data QC, and narrative generation.
• Participate in validating, presenting, and defending AI-derived safety data and predictive models in interactions with global health authorities (FDA, EMA) to advance the regulatory acceptance of computational toxicology.

• PhD, DVM, or equivalent in Cell & Molecular Biology, Toxicology, Pathology, Pharmacology, or a related field. Board certification in toxicology is desired.
• 12+ years of experience in nonclinical safety and toxicology in the biotech/pharma industry.
• Demonstrated success in small molecule drug development for oncology and non-oncology indications is required. Additional experience in biologics is a plus.
• A strong interest in, or hands-on experience with, computational toxicology, machine learning applications in safety assessment, or evaluating in silico predictive models.
• Experience in developing biologics and other novel platforms is highly desired.
• Proven track record advancing programs from discovery through post-IND clinical development and late-stage registration (NDA/BLA).
• Strong experience selecting, auditing, and managing external CRO vendors for GLP toxicology studies.

Attributes: 

• Enterprise mindset; able to bridge the gap between computational AI teams and traditional drug development.
• A strong enthusiasm for operating in an AI-first environment and leveraging cutting-edge automation in daily workflows.
• Analytical and goal-oriented, with the ability to operate with urgency while maintaining the highest standards of scientific rigor and ethics.
• Strong communicator who can translate complex safety and biomarker and computational toxicology data into clear, audience-appropriate risk assessments, building trust across early development.