We make the development of new medicine more predictable

Biosimulytics provides a predictive technology platform for In Silico Development of new drug molecules. Our solution enables our pharmaceutical and biotech customers worldwide to reduce the risks and increase the speed and success rate of their R&D activities in bringing new medicines to market.

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The Need for Innovation in New Drug Development

The increasing volume and complexity of new drug molecules has been escalating Pharma R&D costs, while generics have reduced the return on investment from R&D activity. The time is now ripe for innovation using new digital technologies and in-silico methods to deliver faster, more efficient drug development processes. Scientific software and AI-enabled digital platforms are already having a major industry impact in Pharma & Life Sciences and this transformation is set to grow and mature strongly over the next 25 years. Our area of focus is on Crystal Structure Prediction (CSP) for small molecules using predictive modelling to identify, select and de-risk the physical form of a new drug molecule which is hugely complicated due to polymorphism.

Crystallisation and polymorph control is a persistent headache for the pharmaceutical industry. A candidate drug molecule may appear in several different forms with potentially very different properties which make the end drug product less effective or even harmful.

Predicting the different forms and polymorphs of new molecules through lab experimentation work alone is near impossible and full of uncertainty and risk, leading to lots of wasted time and materials in the development process.

Polymorph screening is mandatory for every new candidate drug molecule to achieve regulatory compliance for clinical trial and beyond as an approved medicine, as well as for patent protection since different forms of the molecule may be used to circumvent a patent.

In Silico methods for virtual polymorph screening are a gamechanger when used together with experimentation, especially if the predictive technology is suitable for early use in the lead optimisation and preclinical stages for a right-first-time approach.

Introducing our CHEMINA™ platform

Accurate prediction of crystal forms

Automated for speed and efficiency

Highly secure, cost effective and sustainable

Modular and flexible to solve real-world problems

Using the CHEMINA platform-as-a-service

We can simulate and predict the 3D crystal structures and polymorphic forms of candidate drug molecules from the most basic 2D chemical diagram inputs

Preclinical screening for competing form risk assessment

Our CHEMINA platform is tailored as a fast, affordable and scalable solution suited to preclinical use for in-silico competing form risk assessment. By generating a comprehensive energy-density polymorph landscape using advanced Crystal Structure Prediction (CSP) techniques, CHEMINA identifies all thermodynamically accessible forms of an API. This enables early insight into which polymorphs are likely to emerge and their relative stability. Since lower-energy forms tend to be more stable but less soluble, while higher-energy forms may offer better solubility, understanding this relationship helps our clients balance manufacturability and bioavailability. CHEMINA’s predictive power allows for informed decision-making, reducing late-stage development risks and accelerating the path to clinical success.

Clinical stage screening for IP patent and manufacturing risks

Our CHEMINA platform contains all of the powerful components necessary to perform a full Crystal Structure Prediction (CSP) on a target molecule which is successfully advancing through clinical trials and needs detailed CMC analysis to ensure that there are no surprises or risks in new forms or polymorphs appearing which could be disastrous for manufacturing at scale and/or for full coverage of the IP and patent on the new drug. Starting with the anhydrate free-base compound, we provide a full picture of the polymorphic landscape covering the full range of symmetry and space groups, matching to experimental results to ensure nothing is missed. Our expertise and capabilities also extend to multi-component compounds (hydrates/solvates, co-crystals, salts).

About Us

Biosimulytics is an award-winning spin-out company from University College Dublin (UCD) in Ireland. Since 2019, we’ve grown from a small founding research team to a rapidly expanding company with a diverse multinational and multidisciplinary team working with leading pharma/biotech clients, CROs/CDMOs and strategic technology partners worldwide. Our ethos is to work collaboratively with our partners and customers to provide deeper data insights for Drug Form Selection and De-Risking earlier in the drug development process and enhance work on API crystallization and solid-state analysis that is still heavily reliant on lab experimentation work. As a result, we enable smarter decision-making for our pharma/biotech clients to get more candidate drugs to market faster with reduced risk.

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Award winner of EIC Accelerator placing us amongst the top 5% of European deeptech ventures

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Meet the Team

Peter F Doyle

CEO & Co-Founder

Peter is a highly experienced co-founder, senior executive and business coach in high-tech ventures across Life Sciences and other industry sectors operating across Europe, US and Asia, including a previous IPO on LSE and NASDAQ.

Johannes Eiglsperger

CTO

With a PhD in Physics and a strong foundation in life science, quantum physics and chemistry, High-Performance Computing, and AI/ML integration, Johannes leads our efforts with strategic vision and technical expertise.

Harish Jangra

Computational Chemist

With a PhD in Theoretical Organic Chemistry and over a decade of industry experience in predictive modelling, quantum chemistry, and pharmacoinformatics, Harish uniquely bridges scientific computing and AI to accelerate in-silico drug development methods.

Lorella Spiteri

Computational Chemist

Lorella holds a PhD in Computational Crystallography and brings deep expertise in molecular modelling, with a focus on polymorphism and co-crystallization in pharmaceutical compounds.

Christian Burnham

Head of R&D & Co-Founder

Christian is a physics graduate from Imperial College in London with extensive scientific research and publications in the field of molecular simulation working in the US and the original lead developer of the company's core technology.

Hugo Rossignol

Computational Scientist

Hugo holds a PhD in Computational Physics from Trinity College Dublin and brings strong expertise in electronic structure modelling, machine learning, and high-performance computing.

Jarlath Dolan

Software Engineer

With a Masters in Electronic Engineering from University College Dublin, Jarlath also brings years of multinational industry experience in high-performance software development and quality assurance for advanced hardware systems.

Niall English

CSO & Co-Founder

Niall is a Full Professor in Chemical Engineering with previous industrial experience working in molecular simulation and drug design in both the US and UK.

Claire Costello

Head of Finance

Claire is a Chartered Accountant with over 12 years’ experience in financial management, client strategy, and operational leadership, supporting strong commercial decisions and scalable growth across diverse sectors.

Petro Visage

Business Development Associate

Petro is a Global Business Foundation Scholar from Trinity College Dublin, bringing expertise in strategic communications, PR, and brand development together with high levels of energy, passion and creativity for sharing our vision.

Join our growing team

We are continuously looking for talented scientists and innovators with a passion for making a real impact in the world to join our team.

Enquire now