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Beyond consulting is your trusted partner in oncology and inflammation PK/PD modelling. We help drug discovery and development projects to design the right experiment, articulate results with all accessible data, and generate compelling evidence by strengthening the link between preclinical models and clinical data using proven innovative modelling.


consulting ltd.



Data and clarity.

Company decision makers, regulators and companies that acquire promising drugs want to know not only what the drug does, but also how good the data are supporting these claims. Designing a new molecule for a target, or performing pharmacological studies for compound selection, is tough enough without having to become an expert in mathematical and statistical modelling as well to ensure the right experimental design and data interpretation to satisfy picky company heads, experienced regulators or savvy investors.


The problem is, to get the full range of modelling services (i.e. population PK/PD, quantitative systems pharmacology, preclinical and clinical statistics) you need to support a project throughout drug discovery and development, you often have to work with large consulting firms that either torture your data to fit their over-simplified, preconceived "generic" models so that their junior modellers can turn the handle to deliver half a dozen projects or more a year without spending any time thinking your problem through, or confuse you with unnecessarily large (often sold as “mechanistic”) models built on shaky data from unverifiable studies reported over a few decades so that they can get renewed contract, let alone these would cost you an arm and a leg, and you cannot expect any useful insights from these models to help you design the right experiments to get to key answers quickly.


No more.


Since 2011, I have been generating compelling experimental evidence by developing, validating and improving predictive models for over a dozen oncology drug projects at different stages at leading pharmaceutical companies. My work has generated the much-needed clarity for prioritising compounds, experiments and projects for different levels of decision making, and it has been recognised by the Oncology iMed Innovation and Achievement Award at AstraZeneca (from Head of Oncology innovative Medicines & Early Development Susan Galbraith) and as numerous breakthroughs by the Research Portfolio Committee (internal governance board) at Boehringer Ingelheim.


I am a trusted advisor on mathematical and statistical modelling who has collaborated with over 100 chemists, biologists, pharmacologists and statisticians within big pharmas. I created, led and grew the Oncology PK/PD modelling lab at BI in recent years.

If you are exploring a new therapeutic concept and defining PoM, PoP and PoC criteria, or if you are advancing your drug project to the IND stage to trigger clinical studies, I would like to hear from you.

You Tao*,  PhD, MSc, BE 

* This is a Chinese name. Please address me by my first name Tao.



Who are our typical clients? 

Medicinal chemist, computational chemist

• What is the target compound profile that meaningfully modulates the intended target?

• Do I need to optimise potency further or should I focus on DMPK properties?

• When does it make sense to nominate a compound for in vivo proof of mechanism?

Screening scientist

• How do I convince the management the target is validated?

• How do I maximise the value of my in vitro assay to inform in vivo studies?

Biomarker scientist

• Have I selected the right target engagement and pharmacology biomarkers?

• How much clinical biomarker changes (degree and duration) do I need to achieve meaningful pharmacological activity of the treatment?


• Does my data package confirm the therapeutic concept?

• What is a valid target compound profile supported by clinical evidence?

• Do I need a combination partner and why?

• What is the right combination partner to deliver clinical efficacy?

• What should be the target objective response criteria and why?

DMPK scientist

• How do I show my PK hypothesis is supported by different in vitroin vivo and clinical studies?

• How I do estimate human PK and eventually human dose for first-in-men study?

Project managers, investors

• What is the minimum preclinical efficacy required to qualify the treatment as a potential clinical success?

• Should I worry about the apparent inconsistency among different types of data?

• What is the one killer experiment I need to see to show this treatment excels in competition?

• Does the value proposition make sense?

PK/PD modeller, pharmacometrician

• Is the published model I am interested in good enough to support decision making?

• Which clinical studies can I use to design a meaningful translational studiy?

• Which is the most representative xenograft model for the intended disease treatment and why?



Expertise and services


  • Pharmacometrics: Population PK/PD, Non-linear Mixed Effects, Synergism, MABEL, TMDD

  • Clinical Statistics: Survival Analysis

  • Bioinformatics: Gene Signature (Regression/Bayesian Methods), Clustering, Data Visualisation

  • Systems Pharmacology: Cancer Signalling (e.g. EGFR, RAS, ERK, WNT, PTEN-p53-MDM2, ATM, WEE1, STING), Cell Cycle-based Modelling, Multi-scale Tumour Growth Modelling

  • Cancer Drug Discovery & Development: Immunotherapy, Cell-directed Targeted Therapy, Chemotherapy, Radiotherapy

  • Programming: R, Python, MATLAB, Mathematica, Fortran, WinNonLin, NONMEM, SAS, C, C++, JAVA


  • Preclinical/Clinical Experimental Design: Define and support Proof of Mechanism, Proof of Principle and Proof of Concept strategies, Assay design

  • Evaluation of Drug Combination: Quantify in vitro and in vivo synergism, Select combination partner based on in vivo and clinical information

  • Back Translation-based Analysis: Evaluate and select tumour models for a particular indication, Simulate clinical trial to explore possible Phase II Overall Response Rate

  • Human Dose Estimation: Human PK Prediction, PBPK-based modelling of special populations

  • Biomarker Selection: Drug sensitivity gene signatures, Efficacy biomarkers, Target engagement biomarkers

  • Regulatory Documentation: IND, NDA

What do others say?

James Yates

Principal Scientist, AstraZeneca

"In recent times Tao has expanded his work into quantitative systems pharmacology - the integration of mechanistic models of biology at a cellular level with drug effect and pharmacokinetics. This has resulted in real insight into the use of anti-cancer agents and has given him good experience with drug discovery data..." 

Gary Wilkinson

Director Clinical Pharmacology, Bayer

"Tao is a talented PK/PD modelling and simulation expert... Tao's models have facilitated a translational approach between the non-clinical and clinical arena, as well as providing an understanding of how clinical proof of mechanism might be achieved. I've found working with Tao really enjoyable..."

Anchor Contact

Ask a question

I hope this answers most of your questions. If not, please send an e-mail or leave me a voicemail message, and I will reply within 24h, even when I am on the road. Most of the time it is a lot quicker than that! I am always willing to spend up to a half-hour discussing your situation without any charge. If I cannot help you with your business, I will be happy to refer you to a qualified professional in your area without charge, obligation, or "referral fees" of any kind.

Good luck in your projects, and in all your endeavours!

Ways of getting in touch:

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