Research Lead / Senior Scientist (DMPK), London

Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-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 drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases.

We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design.

Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.

At Isomorphic Labs, DMPK Leads drive the DMPK strategy of drug discovery projects to deliver high quality clinical candidates whilst using and contributing to the optimisation of state-of-the-art computational and AI ADME models. 

As part of the Drug Design and Medical Research team and through close collaboration with the Technology teams, you will be supporting the business alongside world leading AI/ML Drug Design Platform teams. You will collaborate to deliver scientific expertise and strategic direction to drive both improvements in the Platform and apply this to real drug design projects. 

If you are a skilled and ambitious scientist looking to take the next step in your career, joining Isomorphic Labs will lift you out of your comfort zone and provide you with an amazing opportunity for personal growth and development.

• Experience with biologics, peptides and other new modalities.
• Define and implement stage-appropriate DMPK and ADME strategies across multiple modalities
• Utilise state-of-the-art modelling (e.g., ML/AI and PBPK) to extrapolate preclinical data and predict human dosing, efficacy, and safety windows
• Experienced author and reviewer of DMPK regulatory documents and experience in responding to regulatory queries
  
  

• →Design and implement stage-appropriate DMPK strategies with AI-first approach, integrating quantitative pharmacology and overall project strategies.
• →Design screening cascade and mechanistic experiments to support project progression in a data-driven manner.
• →Integrate DMPK, PD and toxicological data to extract decision-making information, including dose and safety window predictions.
• →Define Quantitative Pharmacology strategy in collaboration with Pharmacology Leads.
• →Optimise the use of Iso’s datasets to address fundamental DMPK questions and advance the field.
• →Optimise molecule design based on physico-chemistry and biotransformation knowledge in collaboration with Chemistry Leads.
• →Maintain knowledge of state-of-the-art technologies and methods to increase confidence in human PK prediction.
• →Author DMPK sections of regulatory documents.
• →Embrace and champion a culture of inclusion and continuous professional development.

• PhD in either Pharmaceutical Science, Pharmacy, Chemistry, or another relevant subject.
• 8+ years’ professional experience as a DMPK Lead, solving DMPK-related problems in drug discovery with a track record of working collaboratively to deliver high quality candidates.
• Experience in supporting DMPK across multiple modalities.
• Comprehensive understanding of drug metabolism, pharmacokinetics, PKPD principles, and translational research.
• Practical experience developing DMPK and quantitative pharmacology packages to support early clinical development, including authoring and reviewing regulatory documents, ideally in oncology or immunology.
• Experience of partnering closely with Preclinical and Clinical teams.
• Demonstrated cross-functional leadership and exceptional interpersonal, communication, and collaborative problem-solving capabilities.
• In depth knowledge of biotransformation.
• Experience of utilising and applying NAMs to further project understanding
• Strategic thinker with strong communication skills, capable of working across multiple disciplines

• Advanced knowledge of PKPD modelling.
• Good understanding of machine learning techniques.
• Familiarity with R, Python and KNIME.

We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it. 

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