Associate Director, Quantitative Pharmacology at Dyno Therapeutics

Waltham, Massachusetts, United States

Dyno Therapeutics Logo
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Biotechnology, PharmaceuticalsIndustries

Requirements

  • PhD, PharmD, or equivalent training in Quantitative Pharmacology, Pharmaceutical Sciences, Engineering, Physics, Applied Mathematics, and/or Computational Sciences
  • 8+ years of bio/pharma experience
  • Based in Waltham, MA (not remote)

Responsibilities

  • Provide strategies and plans for quantitative data analytics (pharmacometrics, population PK/PD analyses, mechanistic drug-disease modeling, meta-analyses, data mining), in alignment with Regulatory requirements as well as corporate and R&D goals, enabling advancement of Dyne programs across all stages of drug development
  • Provide expertise and guidance on quantitative aspects, including dosing strategies and PK/PD, to R&D program teams alongside Clinical Pharmacology and Biomarker Leads, collaborating with Medical, Biometrics, Pharmacovigilance, Preclinical Tox, and ADME/DMPK SMEs
  • Provide hands-on quantitative data analyses, including PK/PD modeling and related tools, supporting program pipeline progression from preclinical to clinical and early to late clinical development
  • Lead the department in establishing a fit-for-purpose internal PK/PD modeling workflow environment, from data inception to model building, qualifying, and simulations, enabling internal PK/PD analyses and interfacing with external modeling CROs
  • Identify and manage consultants and vendors to support M&S activities
  • Author high-quality regulatory documents
  • Ensure adherence to agreed timelines and budgets for execution of deliverables from Clinical Pharmacology studies and programs
  • Collaborate cross-functionally with all relevant areas to support corporate objectives

Skills

Pharmacometrics
PKPD
QSP
PBPK
Mechanistic Modeling
Data Mining
Quantitative Analytics
Modeling and Simulation
Biomarker Modeling

Dyno Therapeutics

Develops AI-optimized gene therapy vectors

About Dyno Therapeutics

Dyno Therapeutics focuses on advancing gene therapy by utilizing Artificial Intelligence to create Adeno-associated virus (AAV) vectors. These vectors are essential tools for delivering genetic material into cells, which is crucial for effective gene therapy. The company's AI technology enables the design and optimization of these vectors, potentially enhancing the success of gene therapies. Dyno collaborates with major pharmaceutical and biotech companies, such as Astellas, Roche, Sarepta, and Novartis, to develop therapies for various diseases affecting the skeletal and cardiac muscles, central nervous system, liver, and eyes. Unlike many competitors, Dyno's unique approach leverages AI to improve the performance of AAV vectors, setting it apart in the biotech field. The company's goal is to improve gene therapy outcomes through its advanced vector technology, ultimately benefiting patients with serious health conditions.

Watertown, MassachusettsHeadquarters
2018Year Founded
$106MTotal Funding
SERIES_ACompany Stage
AI & Machine Learning, Biotechnology, HealthcareIndustries
51-200Employees

Benefits

Remote Work Options

Risks

Gene therapy investment slowdown may impact Dyno's growth and innovation.
Manufacturing bottlenecks could hinder scaling of Dyno's operations.
Increased competition from companies like Form Bio challenges Dyno's market position.

Differentiation

Dyno uses AI to design optimized AAV vectors for gene therapy.
Their AI-driven CapsidMap platform enhances AAV vector development for muscle gene therapies.
Partnerships with major pharma companies like Astellas and Roche boost Dyno's market presence.

Upsides

AI-driven capsid design improves delivery efficiency and reduces manufacturing costs.
Collaboration with NVIDIA enhances biological sequence design for gene therapies.
Generative AI increases efficiency of eye and brain-targeted capsid delivery significantly.

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