Consultancy in Pharmaceutical R&D

Consultancy

  • Strategy building for product development
  • Using QBD and data science to accelerate R&D
  • Extracting information from data
  • Creating understanding of processes and methods
  • Risk based decision making
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Data Science Service

  • Extract hidden knowledge from existing data
  • Build data based expert systems
  • Predict the value of experiments by simulations
  • Perform risk analysis in development to support decisions
  • Visualise key points for decision making
  • Increase the speed and success rate of research and development

Application Building

  • Use knowledge models and process models in-house
  • Evaluate what-if scenarios for the best strategies and decisions
  • Edge of failure and robustness assessments
  • Augment models by adding data or expertise
  • Create tabular and graphical output
  • Company branding

Scope of Services

  • Formulation development
  • Analytical method development
  • Quality By Design
  • Process development
  • Process scale up
  • Pharmacokinetics and in vitro – in vivo correlation
  • Manufacturing process optimisation

Values

  • Design work with the target in mind
  • Increase the value of experiments
  • Accelerate R&D
  • Simplify complex processes
  • Focus on what is important
  • Make the right decisions

About Empirilogic

Empirilogic is a company I started to apply and expand my experience in pharmaceutical and biotech R&D.

I am a Ph.D. pharmacist with more than 30 years of experience in pharmaceutical and biotechnology product development. Some of the domains I have been working in are: formulation development, assay development, in vivo pharmacology and pharmacokinetics, biotechnology, process development, statistics and data analysis

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Consultancy

  • Strategy building for product development
    • Develop end-to-end strategy for product R&D
    • Map current capabilities for future growth and opportunities
    • Select the best products matching with business targets
    • Setup a strategy to maximise knowledge from effort

     

  • Using QBD and data science to accelerate R&D
    • Setup studies to maximise knowledge
    • Apply Quality By Design principles
    • Speed up repetitive data analysis using automation
    • Achieve consistency of data processing and analysis

     

  • Extracting information from data
    • Assign value to data
    • Find out what data can be added to optimise information density
    • Evaluate superiority and inferiority of processes, methods and products
    • Get answers from high-dimensional models

     

  • Creating understanding of processes and methods
    • Quantify probability and impact of factors on outcome
    • Clear visualisation of relationships and effects
    • Include domain expertise in knowledge models
    • Augmenting models by adding new data and information

     

  • Risk based decision making
    • Predict probability and impact of assumptions and choices
    • Share and discuss quantified risks with stakeholders
    • Make decisions based on clear understanding