tl;dr

General Proximity is a seed-stage startup developing the next generation of induced proximity medicines (IPMs). Our OmniTAC drug

discovery engine furnishes molecules that co-opt existing cellular machinery to overcome therapeutic challenges, which have

remained unapproachable to other modalities for decades.

We are seeking a first-rate [https://www.youtube.com/watch?v=Uyzqmn8Azuo] DMPK expert to help us pioneer this uncharted frontier

of drug discovery.

Our Story

A long-standing challenge in drug discovery is the development of molecules capable of modulating difficult or "undruggable"

targets. Disease-causing proteins can be dysfunctional in many different ways, but our armamentarium for fixing them is quite

limited. The most common mechanism of action for FDA-approved drugs is inhibition[1]

[https://www.nature.com/articles/nrd.2016.230], but there are many other possible perturbation types whose potential remains

unrealized.

General Proximity is a seed-stage drug discovery company developing a novel platform technology to solve this problem. We make

bifunctional drugs that induce the modification of drug targets by existing cellular machinery (rather than through direct

modulation by the drug, the classical approach).

Historically, the development of technologies that allow one to push new buttons in biology has been an incredibly fertile field

for the discovery of new medicines[2 [https://www.nature.com/articles/nrd3410], 3 [https://www.nature.com/articles/nrd.2016.213],

4 [https://www.nature.com/articles/nrd.2016.211]], and our technology holds the same promise.

The Position

We are seeking an exceptional DMPK expert to join and lead our drug metabolism and pharmacokinetics function. This is a hands-on,

high-impact role in which you will design and execute DMPK studies across our small molecule portfolio, interpret and communicate

data to project teams, and serve as a key DMPK contributor in cross-functional settings.

You will help shape scientific approaches, support regulatory activities, and play an important role in advancing programs from

lead optimization through IND. You will work closely with our medicinal chemistry, structural biology, pharmacology, and

toxicology teams to translate DMPK science into actionable program decisions.

The ideal candidate is a hands-on scientist who combines solid technical expertise in ADME, in vivo PK, and PK/PD modeling with

the ability to work independently and collaborate effectively across teams. This role is well suited for someone with a few years

of DMPK experience at a pharma or biotech who now wants to take on greater ownership and grow at a mission-driven company working

at the frontier of induced proximity medicine.

This role benefits from familiarity with the unique DMPK challenges of induced proximity medicines and bifunctional molecules.

These include non-linear and dose-dependent pharmacokinetics arising from ternary complex formation, linker and warhead metabolic

soft spots, high molecular weight and physicochemical complexity affecting permeability and oral bioavailability, tissue

distribution considerations for proteasome-engaging degraders, and the interpretation of hook-effect phenomena in in vitro and in

vivo settings. Exposure to TPD, molecular glue, PROTAC, or other bifunctional modality DMPK is a plus for this role.

WHAT YOU'LL DO

In Vitro ADME

Design, execute, and interpret in vitro ADME studies, including metabolic stability, CYP inhibition/induction, plasma protein

binding, permeability (Caco-2/MDCK), solubility, and transporter assays.

Contribute to in vitro–in vivo correlation (IVIVC) analyses to inform candidate selection and advance structure–activity/property

relationships.

Interpret metabolic soft spot and MetID data, translating findings into actionable guidance for medicinal chemistry teams.

Support CRO relationships for outsourced ADME studies, including scientific oversight of study execution and data quality review.

Bioanalytical Sciences

Support bioanalytical activities for the portfolio, including CRO-performed LC-MS/MS method development for small molecules and

their metabolites across biological matrices.

Help ensure GLP-compliant bioanalytical practices for IND-enabling studies and monitor regulated bioanalysis timelines and data

quality through CRO partners.

Contribute to fit-for-purpose bioanalytical approaches for induced proximity molecules, including strategies for quantifying

bifunctional compounds and target engagement biomarkers.

In Vivo Pharmacokinetics

Design and support in vivo PK studies across rodent and non-rodent species, including study design, data interpretation, and

cross-program learnings.

Perform high-quality PK data analysis (NCA and compartmental) using Phoenix WinNonlin or equivalent, ensuring accurate reporting

and data integrity.

Integrate PK data with pharmacology and toxicology readouts to inform candidate progression criteria and target product profiles.

Coordinate with CROs for in vivo studies, tracking scope, timelines, and scientific deliverables.

PK/PD Modeling & Simulation

Perform PK/PD modeling and simulation, including PBPK modeling (Simcyp, GastroPlus) and allometric scaling to support human PK

prediction.

Apply quantitative pharmacology approaches to support translational decision-making, FIH dose selection, and clinical dose range

prediction.

Use modeling and simulation to inform go/no-go decisions and communicate DMPK findings to project teams.

Present DMPK modeling results in cross-functional project team meetings.

Regulatory & IND-Enabling Work

Support DMPK execution for IND-enabling programs, including study design, drafting of study reports, and data package delivery.

Contribute to DMPK sections of IND and CTA submissions; author and review relevant study reports and document sections.

Support preparation of DMPK materials for interactions with regulatory agencies, including briefing documents.

Maintain working knowledge of current regulatory guidance (DDI, MIST, bioanalytical method validation, ICH M9/M10) and apply

evolving standards.

Collaboration & Cross-Functional Contribution

Contribute to DMPK team goals and priorities in alignment with company objectives and pipeline evolution.

Serve as an active member of cross-functional project teams, contributing DMPK input to program planning and decision-making.

Support DMPK input for scientific evaluations and collaborations as needed.

Support clinical pharmacology activities as programs advance toward IND, including FIH dose projections, DDI risk assessment, and

exposure–response analysis; contribute to clinical pharmacology sections of regulatory documents.

Help track CRO spend and study timelines in alignment with program milestones.

Author and present scientific findings through peer-reviewed publications, conference abstracts, and posters; contribute to

General Proximity’s scientific credibility and platform visibility in the induced proximity field.

ABOUT YOU

High Agency. Initiative, independence, and self-accountability are some of our most valued traits.

Enthusiastic. We love people who are excited about what they are doing and are generally attempting to build a high-energy team.

Intensity and Grit. Early-stage startups are hard. Drug discovery is doubly so. We are looking for candidates who have a

demonstrated ability to stick with complex problems for the long haul, with a team that has your back along the way.

Prosocial. We are here to create life-saving medicines for the patients who need it most. You should be, too.

QUALIFICATIONS & NICE-TO-HAVES

PhD in pharmacokinetics, pharmaceutical sciences, or a related discipline.
A minimum of 3 years of industry experience in DMPK, spanning drug discovery and development, with a track record of

contributing to small molecule programs.

Demonstrated ability to work independently and collaborate effectively within cross-functional project teams.
Hands-on expertise in in vitro ADME and in vivo PK, with the ability to translate data into actionable drug discovery insights.
Proficiency in PK data analysis (Phoenix WinNonlin or equivalent) and familiarity with PBPK/PK-PD modeling platforms (Simcyp,

GastroPlus, or equivalent).

Experience contributing to IND-enabling DMPK studies and authoring study reports.
Working knowledge of FDA, EMA, and ICH guidance relevant to DMPK (DDI, MIST, M9/M10, bioanalytical validation).
Strong communication and presentation skills, with the ability to clearly convey DMPK science to cross-functional teams.
Hands-on experience with bioanalytical activities, including LC-MS/MS method development in support of DMPK studies.
Working knowledge of clinical pharmacology principles, including FIH dose projection, DDI risk assessment, and

exposure–response analysis, sufficient to support drug development through early clinical stages.

Nice to have:
Experience working in a startup or early-stage biotech environment
Experience contributing to a small molecule program advancing toward or through IND
Experience with novel modalities such as TPD, molecular glues, or PROTACs
Familiarity with AI/ML-based ADME prediction tools and an interest in integrating computational approaches (e.g., ML-driven

metabolic stability or permeability models, digital twins for PK simulation) into the DMPK workflow alongside established

platforms such as Simcyp and GastroPlus

BENEFITS [https://www.generalproximity.bio/benefits]

Strong equity incentives. We are looking for candidates who will bring a strong sense of ownership to drive their project areas

forward, and we believe that you deserve to be compensated accordingly.

Top tier medical, dental, and vision coverage + One Medical membership.
401(k) retirement plans.
Education and health/fitness incentive programs.
Meditation retreats—do a ten-day Vipassana retreat without counting towards vacation days.
Reading budget! We will buy you books. 📚
Located in the MBC BioLabs at 135 Mississippi Street, an entrepreneurial hub full of the best scientists and operators the Bay

Area has to offer. Our lab is a very short walk from the 22nd St Caltrain Station and a number of wonderful restaurants and

cafés.

ABOUT US

Work Hard/Play Hard. We believe time is our most valuable commodity, so we strive to create a culture that reflects this. We won’t

drag you through unnecessary meetings or email you at 7 PM on a Saturday. When we're at work, we're there to get things done, and

when we're off, we're really off. 🌴

Strong Communication. We like well-written documents over PowerPoints, OKRs over vague mission statements, and weekly one-on-ones

over yearly reviews.

Writing First. We have a "writing-first" culture. We believe that clarity of writing reflects clarity of thinking and that the

benefits of well-written documentation in a scientific environment are innumerable: democratization of ideation and

decision-making, increased reproducibility, quicker scaling and onboarding, and better company-wide alignment, to name a few.

Growth. As an early-stage startup, we value scientists with an independent, can-do attitude. The more hats you can wear, the

better. Our job as employers is to put you in positive feedback loops so you can grow in the direction of your choosing.

---------------------------------------------------------------------------------------------------------------------------------

Title and compensation commensurate with experience. Applications from candidates of diverse backgrounds, women, and members of

underrepresented minority groups are particularly welcomed. We look forward to hearing from you. :)

More info at jobs.generalproximity.bio [https://jobs.generalproximity.bio/]

Roll

Scientist/Sr. Scientist, DMPK

Kategori

Other

Plats

San Francisco, CA

Publicerad

29 juli

Sista ansökningsdag

29 augusti

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Scientist/Sr. Scientist, Computational Chemistry

General Proximity•San Francisco, CA

TL;DR General Proximity is a seed-stage startup developing the next generation of induced proximity medicines (IPMs). Our OmniTAC drug discovery engine furnishes molecules that co-opt existing cellular machinery to overcome therapeutic challenges, which have remained unapproachable to other modalities for decades. We are seeking a first-rate [https://www.youtube.com/watch?v=Uyzqmn8Azuo] computational chemist to help us pioneer this uncharted frontier of drug discovery. ---------------------------------------------------------------------------------------------------------------------------------- OUR STORY A long-standing challenge in drug discovery is the development of molecules capable of modulating difficult or "undruggable" targets. Disease-causing proteins can be dysfunctional in many different ways, but our armamentarium for fixing them is quite limited. The most common mechanism of action for FDA-approved drugs is inhibition[1] [https://www.nature.com/articles/nrd.2016.230], but there are many other possible perturbation types whose potential remains unrealized. General Proximity is a seed-stage drug discovery company developing a novel platform technology to solve this problem. We make bifunctional drugs that induce the modification of drug targets by existing cellular machinery (rather than through direct modulation by the drug, the classical approach). Historically, the development of technologies that allow one to push new buttons in biology has been an incredibly fertile field for the discovery of new medicines[2 [https://www.nature.com/articles/nrd3410], 3 [https://www.nature.com/articles/nrd.2016.213], 4 [https://www.nature.com/articles/nrd.2016.211]], and our technology holds the same promise. THE POSITION We are seeking an exceptional computational chemist to support our computational chemistry, cheminformatics, and molecular design efforts. This role will help drive small-molecule drug discovery programs by providing practical modeling support, applying modern computational workflows, and using the cheminformatics and AI-enabled tools that empower medicinal chemists and project teams. The successful candidate will be a hands-on drug designer: someone who can partner closely with medicinal chemists, structural biologists, biologists, and DMPK scientists to guide compound design from hit identification through lead optimization and candidate selection. They will also apply practical tools that improve decision-making, accelerate design-make-test-analyze cycles, and make computational and AI-driven methods accessible to bench chemists. The ideal candidate is a computational drug hunter who combines strong technical expertise with practical medicinal chemistry judgment. This person should not be an isolated modeler, but a true project partner who sits with chemistry teams, understands the design problem, proposes molecules, helps interpret data, and contributes tools that make the broader organization faster and smarter. This role is ideal for someone who has worked in a pharma or biotech computational chemistry group and wants to work with modern, AI-enabled computational methods while remaining directly involved in molecule design. WHAT YOU'LL DO Computational Chemistry and Molecular Design Provide hands-on computational chemistry support to small-molecule discovery programs from target evaluation, hit identification, hit-to-lead, and lead optimization through candidate nomination. Apply structure-based and ligand-based design approaches to guide compound design, including docking, molecular dynamics, pharmacophore modeling, QSAR, scaffold hopping, virtual screening, FEP/free-energy methods, and multi-parameter optimization. Use structural biology data, including X-ray structures, cryo-EM structures, homology models, and AlphaFold-derived models, to generate actionable design hypotheses. Partner with the medicinal chemistry team to interpret SAR, optimize potency, selectivity, physicochemical properties, ADME/PK, developability, and synthetic feasibility. Contribute to computational design discussions with project teams and translate complex modeling results into clear, practical medicinal chemistry recommendations. Support portfolio prioritization by evaluating target tractability, ligandability, binding-site quality, chemical matter, and developability risks. Cheminformatics and Data Infrastructure Use and help improve chem and bioinformatics tools that support compound registration, structure-searching, SAR analysis, property visualization, compound triage, library design, and project decision-making. Apply tools for chemical data handling, including similarity and substructure searching, R-group analysis, matched molecular pairs, reaction enumeration, compound clustering, property prediction, and visualization. Work with internal or external engineering and data science teams to integrate chemical, biological, DMPK, structural, and assay data into usable project dashboards and design tools. Follow best practices for chemical data quality, assay data curation, compound annotation, metadata standards, and reproducible computational workflows. Use commercial and open-source computational tools, including platforms such as Schrödinger, MOE, CCDC tools, ChemAxon, KNIME, Pipeline Pilot, RDKit, DataWarrior, Spotfire, and related systems. AI/ML and Digital Chemistry Tools Apply user-friendly AI/ML-enabled molecular design tools, including generative chemistry, predictive ADME/Tox models, property prediction, active learning, virtual screening, and decision-support systems. Help incorporate AI tools into the DMTA cycle, including compound prioritization, library design, synthetic route ideation, molecular-property prediction, and design hypothesis generation. Support AI literacy across chemistry and project teams by helping colleagues understand appropriate use, limitations, and interpretation of predictive models. Help develop workflows that allow medicinal chemists to use modeling and AI tools without requiring deep computational expertise. Collaboration and Continuous Improvement Contribute to the computational chemistry approach for projects and align it with discovery program needs. Serve as a subject-matter resource for computational chemistry, cheminformatics, AI-enabled design, and molecular modeling. Support collaborations with CROs, software vendors, academic groups, and computational chemistry consultants where appropriate. Represent computational chemistry in project team meetings and program discussions. Maintain awareness of emerging computational, AI, and cheminformatics technologies and recommend adoption where scientifically and operationally justified. ABOUT YOU High Agency. Initiative, independence, and self-accountability are some of our most valued traits. Enthusiastic. We love people who are excited about what they are doing and are generally attempting to build a high-energy team. Intensity and Grit. Early-stage startups are hard. Drug discovery is doubly so. We are looking for candidates who have a demonstrated ability to stick with complex problems for the long haul, with a team that has your back along the way. Prosocial. We are here to create life-saving medicines for the patients who need it most. You should be, too. QUALIFICATIONS & NICE-TO-HAVES * PhD in Computational Chemistry, Medicinal Chemistry, Chemical Physics, Biophysics, Cheminformatics, Physical Organic Chemistry, or a related discipline. * A minimum of 3 years of relevant experience in pharma, biotech, or a drug discovery-focused research environment. * Track record of using computational chemistry to impact small-molecule drug discovery programs, ideally through hit-to-lead or lead optimization. * Hands-on expertise in structure-based drug design, ligand-based design, docking, molecular dynamics, virtual screening, QSAR, FEP/free-energy methods, pharmacophore modeling, and multi-parameter optimization. * Strong working knowledge of medicinal chemistry principles, SAR interpretation, physicochemical property optimization, ADME/PK concepts, and developability considerations. * Practical experience with cheminformatics platforms, chemical databases, chemical data curation, compound registration systems, and project-facing visualization tools. * Experience with AI/ML applications in molecular design, including predictive modeling, generative chemistry, active learning, or AI-enabled compound prioritization. * Strong programming or scripting ability, preferably Python, with experience using cheminformatics toolkits such as RDKit and modern data science workflows. * Ability to communicate complex computational concepts clearly to medicinal chemists, biologists, and non-specialist stakeholders. * Ability to collaborate within cross-functional teams and influence project decisions through strong scientific input. * Nice to have: * Experience working in a biotech or fast-moving discovery organization * Experience implementing user-friendly modeling tools for medicinal chemists * Familiarity with cloud-based or high-performance computing environments * Experience with automated DMTA workflows, electronic lab notebooks, compound management systems, assay-data systems, and integrated discovery platforms * Experience supporting discovery across multiple modalities, such as covalent inhibitors, bifunctional molecules, and molecular glues * Familiarity with synthetic accessibility prediction, retrosynthesis tools, reaction enumeration, and library design * Scientific contributions through publications, presentations, patents, open-source contributions, or demonstrated project impact BENEFITS [https://www.generalproximity.bio/benefits] * Strong equity incentives. We are looking for candidates who will bring a strong sense of ownership to drive their project areas forward, and we believe that you deserve to be compensated accordingly. * Top tier medical, dental, and vision coverage + One Medical membership. * 401(k) retirement plans. * Education and health/fitness incentive programs. * Meditation retreats—do a ten-day Vipassana retreat without counting towards vacation days. * Reading budget! We will buy you books. 📚 * Located in the MBC BioLabs at 135 Mississippi Street, an entrepreneurial hub full of the best scientists and operators the Bay Area has to offer. Our lab is a very short walk from the 22nd St Caltrain Station and a number of wonderful restaurants and cafés. ABOUT US Work Hard/Play Hard. We believe time is our most valuable commodity, so we strive to create a culture that reflects this. We won’t drag you through unnecessary meetings or email you at 7 PM on a Saturday. When we're at work, we're there to get things done, and when we're off, we're really off. 🌴 Strong Communication. We like well-written documents over PowerPoints, OKRs over vague mission statements, and weekly one-on-ones over yearly reviews. Writing First. We have a "writing-first" culture. We believe that clarity of writing reflects clarity of thinking and that the benefits of well-written documentation in a scientific environment are innumerable: democratization of ideation and decision-making, increased reproducibility, quicker scaling and onboarding, and better company-wide alignment, to name a few. Growth. As an early-stage startup, we value scientists with an independent, can-do attitude. The more hats you can wear, the better. Our job as employers is to put you in positive feedback loops so you can grow in the direction of your choosing. ---------------------------------------------------------------------------------------------------------------------------------- Title and compensation commensurate with experience. Applications from candidates of diverse backgrounds, women, and members of underrepresented minority groups are particularly welcomed. We look forward to hearing from you. :) More info at jobs.generalproximity.bio [https://jobs.generalproximity.bio/]

Sista ansökan: 29 aug.Publicerad: 29 juli

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This work supports programs like Anthropic’s AI for Science Program [https://www.anthropic.com/news/ai-for-science-program] and our rare disease research grants [https://www.anthropic.com/news/rare-disease-research-grants]. 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Sista ansökan: 22 aug.Publicerad: 22 juli

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Sista ansökan: 29 aug.Publicerad: 29 juli

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