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Services

Strategic and hands-on model-informed drug development, in four areas: clinical development, preclinical and translational PK/PD, PBPK, and virtual trials for complex generics and biosimilars. Underneath them, the PK and TK analysis that we also deliver on its own.

What we offer

Four areas, strategy and execution

In each area we advise on the strategy and we do the modeling ourselves. The same people who shape the plan build the models and write the report.

Strategic and hands-on MIDD for clinical development

A model-informed plan for the clinical programme, and the analyses that carry it out, documented in line with ICH M15.

  • MIDD and clinical pharmacology strategy for the development plan
  • Clinical study NCA, with TFLs and ADaM PK datasets for submission
  • Population PK/PD and exposure-response for dose selection and justification
  • Clinical trial simulation to test designs before they run
  • Submission-ready reports, briefing documents and responses to regulators

Preclinical and translational PK/PD modeling

From animal data to a human dose you can defend.

  • PK/PD and toxicokinetic analysis of preclinical studies
  • Exposure-based safety margins for the IND or CTA
  • Animal-to-human translation and human PK prediction
  • First-in-human starting dose and escalation rationale

PBPK modeling

Predicting exposure where it has not been measured, to decide which clinical studies are still needed.

  • Drug-drug interaction assessment
  • Organ impairment, paediatrics and other special populations
  • Formulation, absorption and food effect (PBPK/PBBM)
  • Model verification documented to the standard regulators expect

Virtual BE and PK-similarity trials

Bioequivalence for complex generics and PK similarity for biosimilars, simulated before the pivotal study is committed.

  • Virtual bioequivalence by PBPK/PBBM for complex generic products
  • Design and simulation of PK similarity studies for biosimilars
  • Sample size, sampling schedule and study population chosen on evidence
  • The risk of a failed study quantified before it runs
Core PK services

PK and TK analysis

Non-compartmental analysis and toxicokinetics for preclinical and clinical studies, delivered as a standalone package or as the base of a modeling programme.

  • NCA for clinical studies, from first-in-human onward
  • TK analysis of GLP and non-GLP toxicology studies, single and repeat dose
  • Exposure-based safety margins against the toxicology
  • Tables, figures and listings (TFLs) for the clinical study report
  • CDISC ADaM PK datasets, such as ADNCA and ADPP, ready for submission
How we run NCA and TK

Across the programme

The decision at each stage

Each stage of development asks a different question. This is where each service area comes in.

  1. 01

    Candidate and formulation

    Which candidate, and which formulation, gives the exposure the programme needs?

    Translational PK/PDPBPK
  2. 02

    Preclinical and IND-enabling

    Are the safety margins adequate, and what exposure should we expect in humans?

    Translational PK/PDPK and TK analysisPBPK
  3. 03

    First in human

    What is a safe starting dose, and how fast can we escalate?

    Translational PK/PDPK and TK analysisClinical MIDD
  4. 04

    Clinical development

    Which dose, for which patients, goes into the pivotal trial, and which clinical pharmacology studies are still needed?

    Clinical MIDDPK and TK analysisPBPK
  5. 05

    Submission

    Is the dose justified for every patient group that will be treated?

    Clinical MIDDPBPK
  6. 06

    Generics and biosimilars

    Will the product be bioequivalent, or PK-similar, to the reference, and how should the pivotal study be designed?

    Virtual BE

Methods

The methods behind the four areas

The method follows from the question and the data that exists. Most programmes use more than one.

Non-compartmental analysis (NCA)

The fastest, cheapest way to get an answer out of PK data, and the standard PK analysis of every clinical study. Right as a first read on preclinical data, as the PK section of a clinical study report, and as the base before moving to a population model.

  • Standard PK parameters for decision making, preclinical and clinical
  • Exposure-based safety margins against the toxicology
  • Clinical study NCA with tables, figures and listings (TFLs) for the clinical study report
  • CDISC ADaM PK datasets, such as ADNCA and ADPP, ready for submission
Time Concentration Cmax Tmax AUC

Toxicokinetics (GLP and non-GLP)

The exposure side of the toxicology package. This is where a large share of IND-enabling work begins: the tox studies have run, and the concentrations now have to become parameters, safety margins and a report a reviewer will accept.

  • TK analysis of GLP and non-GLP toxicology studies, single and repeat dose
  • Exposure at the NOAEL, and the margin over the predicted human exposure
  • Dose proportionality, accumulation on repeat dosing, and sex differences
  • Sparse and composite sampling designs typical of rodent studies
  • Tables, figures and report written for the nonclinical section of an IND or CTA
Time Concentration Low Mid High NOAEL exposure

Physiologically-based PK (PBPK)

Built from physiology and compound properties rather than fitted to one dataset, so you can move the patient, the formulation or the co-medication and still get a prediction. This is the workhorse for the preclinical-to-clinical step.

  • Animal-to-human translational modeling
  • Formulation, release rate, route of administration and food effect
  • Drug-drug interaction assessment
  • Special populations: renal and hepatic impairment, pregnancy
  • Virtual bioequivalence
Arterial Venous Lung Liver Gut Kidney Muscle Other Elimination: hepatic metabolism and renal excretion

Population PK/PD

For when the question is not what happens on average, but who differs and why. A population model separates variability you can explain from noise that remains, which is what dose adjustment rests on.

  • Covariate assessment (body weight, age, sex, renal function)
  • Exposure-response for efficacy and for safety
  • Study design and sampling schedule optimisation
  • Simulation-based dose recommendation
Depot Central Peripheral Effect Dose ka Q CL

Clinical trial simulation

Testing the design before you pay for it. Simulation shows how much of the outcome rides on your decisions and how much simply on luck, which is a useful thing to know before committing a small company's runway.

  • Custom virtual populations (age, disease status, ethnicity)
  • Impact of unknown factors (variability, dropout, response rate)
  • Probability of trial success across scenarios
  • Comparison of sample sizes and dosing regimens
Time Concentration Target window

Exposure-response modeling

The bridge between pharmacokinetics and what the drug actually does. Most dose questions are really exposure-response questions, and answering them properly is what turns a chosen dose into a justified one.

  • Efficacy and biomarker response as a function of exposure
  • Exposure-safety analysis, including adverse events and laboratory findings
  • Benefit-risk comparison across candidate doses and regimens
  • Dose justification for filing, and support for labelling language
  • Analysis planned prospectively rather than assembled after the fact
Exposure Response EC50 Emax

In vitro-in vivo correlation (IVIVC)

A validated correlation links the dissolution profile to plasma exposure. It is what lets you set dissolution specifications on evidence rather than convention, and it keeps paying back every time the process or the site changes.

  • Level A correlation development, validation and predictability assessment
  • Dissolution specifications grounded in in vivo exposure
  • Support for formulation, equipment, process and manufacturing site changes
  • Release-rate and route optimisation for modified-release products
  • Used for interpolation within the development range, not extrapolated beyond it
% dissolved in vitro % absorbed in vivo line of identity

Concentration-QTc modeling

Cardiac safety read from the relationship between concentration and QT interval, using data you are already collecting in early phase rather than a separate study.

  • C-QTc analysis from first-in-human and other early-phase data
  • Assessment against the 10 ms threshold of regulatory concern
  • Under the ICH E14 Q&A (R3), a well-conducted analysis can substitute for a thorough QT study
  • Concentration-effect documentation for the clinical pharmacology summary
Plasma concentration ΔΔQTc (ms) 10 ms threshold

Bioequivalence and virtual bioequivalence

For complex generics, biosimilars, and bridging between formulations, strengths or manufacturing changes, with no more clinical work than the evidence requires.

  • Conventional bioequivalence analysis and study design
  • Model-based bridging between formulations and strengths
  • Virtual bioequivalence by PBPK and physiologically-based biopharmaceutics modeling
  • PK similarity study design and simulation for biosimilars
  • Biowaiver strategy, and an honest read on whether it will hold
0.80 1.00 1.25 Geometric mean ratio (test / reference) 80 – 125% acceptance range Cmax AUC0-t AUC0-inf

Not sure which of these you need?

Most programmes do not fall neatly into one stage. Describe where you are and we will tell you honestly what modeling can settle and what still has to be measured.

Book an intro call [email protected]