Independent scientific consultancy and professional education
Veritas Clinical Innovations advises on therapeutic discovery and development, clinical study design, AI-enabled research and scientific due diligence, and teaches cardiovascular risk prediction, the science of healthy ageing, periodontology and AI in research through live online courses.
Confidential expert advice for teams developing therapies, designing studies and testing whether the science holds.
Live online programmes in AI-based cardiovascular risk prediction, the science of longevity, periodontology and AI in clinical research, in English and Polish.
The Veritas approach
We work from primary literature, trial registries and your own data rather than from assumptions. Every engagement is scoped in writing, led personally by the named expert and delivered as advice you can act on, never as a promise of results.
Assessments quote the studies, registries and guidelines they rest on, so your team can check every claim.
The professor you speak to is the person who does the work. Nothing is delegated to unnamed associates.
We provide independent scientific advice. We do not provide medical care, regulatory representation or legal advice.
Consulting
Particular depth in cardiovascular disease, with relevance to oncology and respiratory medicine.
From target rationale to a credible development plan: mechanism review, translational evidence, candidate positioning and the studies that will be asked for next.
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Endpoints, populations, comparators and statistical framing that hold up to scientific, ethics-committee and regulatory scrutiny.
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Where machine learning and language models genuinely add value in recruitment, phenotyping, monitoring and analysis, and where they do not.
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Independent, evidence-graded assessment of a therapy, biomarker, device or research programme for investors, boards, counsel and institutions.
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A fixed-scope, registry-sourced brief on every registered trial for a named target, mechanism or indication, delivered in five working days.
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What your competitors and adjacent markets have already proved, read by clinicians and scientists, tested for transfer and turned into a plan your board can run.
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Analysis of your clinical, imaging and registry data using Bayesian and machine-learning methods developed by Professor Arkadiusz Sitek, from exploratory modelling to validated prediction, delivered with the code, the uncertainty and the limitations stated.
LearnOffer for companies
Comparator is constructive competitor analysis for pharmaceutical, biotech and diagnostics companies of every size: what the market has already learned, read by clinicians and scientists, tested for transfer and turned into a plan with a measured pilot.
Explore ComparatorLive online learning
Small live cohorts on Zoom with separate English and Polish sessions. Register interest now; dates and faculty are confirmed with members first.
How machine-learning tools estimate cardiovascular risk from the history, from blood and molecular biomarkers and from imaging, and how to judge whether they work.
Faculty: Professor Tomasz Guzik
A careful, evidence-graded tour of the interventions sold as rejuvenating, decade by decade, separating what is proven from what is promised.
Faculty: Professor Tomasz Guzik, Professor Marta Czesnikiewicz-Guzik
Diagnosis, non-surgical and surgical therapy, and the systemic context of periodontal disease.
Faculty: Professor Marta Czesnikiewicz-Guzik
What machine learning and language models can and cannot do across the study lifecycle.
Faculty: Professor Tomasz Guzik
Insights
Expert notes on clinical research, cardiovascular risk, healthy ageing and emerging therapeutics. Each one points to the original sources.
AI in clinical research
Machine learning is entering trials through recruitment, adjudication and monitoring, yet most tools still lack prospective evaluation. How to tell mature applications from promising ones, and what ethics committees and regulators now expect.
5 min read
Clinical research consultancy
Consultancy is not a contract research organisation and not regulatory affairs. Used at the right moments, it changes the questions a programme asks and the evidence it produces.
4 min read
Advanced hypertension therapeutics
Three new classes have reached late-phase trials: RNA silencing of angiotensinogen, aldosterone synthase inhibition and dual endothelin antagonism. This note separates mechanism, blood-pressure effect and outcome evidence, and says plainly where the last does not yet exist.
9 min read
Experts
Advice and teaching are delivered personally, drawing on decades of translational cardiovascular research, cardiovascular genomics, healthcare AI, genetic epidemiology, periodontology and clinical teaching.
Professor of Medicine · Clinician scientist in cardiovascular medicine and hypertension
Physician and vascular biologist whose work on inflammation and immune mechanisms in hypertension has shaped how the field understands blood-pressure regulation. He advises on therapeutic discovery and development, clinical research strategy, AI-enabled research and scientific due diligence.
Professor of Medical Sciences · Specialist in periodontology and oral surgery
Clinician scientist in periodontology whose research established links between periodontal inflammation, endothelial dysfunction and hypertension. She leads the periodontology programme and advises on oral–systemic research and clinical study design in dentistry.
Professor of Cardiovascular Medicine · Clinician scientist in hypertension, cardiovascular genomics and kidney biology
Physician and clinician scientist whose work on the genetic mechanisms of hypertension and kidney disease, and on objective testing for non-adherence to blood-pressure treatment, has changed how difficult hypertension is investigated and managed. He advises on cardiovascular genomics, difficult-to-treat hypertension, clinical trial design and translational research strategy.
Physicist and healthcare AI researcher · AI and Bayesian methods trained and developed at Massachusetts General Hospital and Harvard Medical School
Physicist and healthcare AI researcher whose machine-learning and Bayesian methods were trained and developed at Massachusetts General Hospital and Harvard Medical School, from PET and SPECT reconstruction to foundation models of electronic health records. He advises on AI-driven data analysis, imaging quantification and the validation of clinical prediction models.
Genetic epidemiologist · Mendelian randomisation, population genetics and immune mechanisms of hypertension
Molecular biologist turned genetic epidemiologist, trained in the Netherlands and at Harvard Medical School, whose Mendelian randomisation studies in UK Biobank established causal roles for immune cells in blood-pressure regulation and for elevated blood pressure in brain changes and cognitive impairment. He advises on genetic epidemiology, population and biobank studies and causal inference from large datasets.
Professors Tomasz Guzik, Marta Czesnikiewicz-Guzik, Maciej Tomaszewski, Arkadiusz Sitek and Mateusz Siedliński advise through Veritas Clinical Innovations in an independent, personal capacity. Their advice does not represent, and is not endorsed by, any university, journal, professional society or employer.
Describe your project in a few sentences or book a 20-minute introductory call. We aim to respond within two business days.
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