Interdisciplinary Capabilities

The Applied BioMath team has deep expertise in the areas of mathematics, modeling, and biology.  We leverage this expertise as we apply our modeling approach to various therapeutic modalities, including both large and small molecules, as well as a lengthy list of indications.

 

 

 

  • Semi-mechanistic PK/PD
  • Quantitative systems pharmacology (QSP) model development
  • Quantitative systems toxicology (QST) model development
  • Non-compartmental analysis (NCA) of PK data
  • Toxicokinetic data analysis & report writing
  • Pre-IND and IND writing of PK related sections
  • PK/PD analysis
  • Population PK/PD
  • Biomarker data analysis
  • Bioinformatics
  • Pathway model development & analysis
  • ODE/PDE/SDE
  • Linear Algebra
  • Optimization
  • Machine Learning
  • Sensitivity Analysis
  • Parameter Estimation
  • Probability Statistics
  • Large Molecule
    • Monoclonal Antibody (mAb)
    • Antibody Drug Conjugate (ADC)
    • Engineered Protein
      • Targeted Cytokines
      • Multi-valent Antibody Constructs
    • Bispecific
    • Trispecific 
    • Prodrug
    • T-cell Engagers/BiTEs
  • Small Molecule
    • Protein Kinase Inhibitors
    • Receptor Blockers
    • Modulators of Protein-protein Interaction
    • Transcriptional Regulators
  • Cell Therapies
  • Combination Therapies
  • RNA/RNAi Therapies
  • CRISPR/Cas9
  • Oncology
    • Immuno-oncology
  • Chronic Inflammation
    • Rheumatoid Arthritis
    • Irritable Bowel Disease
      • Ulcerative Colitis 
      • Crohn's Disease
    • Graft-Versus-Host Disease
    • Lupus Erythematosus
    • Idiopathic Thrombocytopenic Purpura
    • Type 1 Diabetes
  • Rare Diseases
  • Neuroscience
    • Migraine
    • Chronic Pain
    • Alzheimer's Disease
  • Cardio Metabolic
    • Type 2 Diabetes Mellitus
    • NASH
    • NAFLD

Proven Results

Working with Applied BioMath enabled us to foresee any hurdles we may have encountered and also ensured we are structuring our trials such that we are targeting the right patients and the right doses.


Mark Currie, PhD
Ironwood Pharmaceuticals

We chose to work with Applied BioMath because of their significant expertise and strength in developing mechanistic QSP models in oncology.


Karim Azer, PhD
Sanofi

Applied BioMath delivered exactly what we asked for in the time frame agreed upfront. Josh and John worked with the team to leverage both internal and external information and develop a 'fit for purpose' model in an eight-week time frame.


Anne Heatherington, PhD
Pfizer