Our vision is to provide an innovative, cost effective, and efficient way to identify new active chemical starting points to feed into early drug discovery programs.

The rise of antibiotic resistance or the increase in dementia related diseases are some examples of the need for new and better medicines. Despite significant effort and enormous amounts of money being spent by Pharmaceutical companies in finding new chemical starting points (so-called hits), the chances of those hits being developed into next generation drugs still remain low. Critically, the identification and quality of the hits are essential to feed into early drug discovery programs, and thus to deliver new and better medicines to the market.

A critical aspect of the hit identification process is the quality of the library and the screening method used in order to increase the chances of finding high-quality hits to progress. The chemical space spanned for potential “drug-like” molecules is astronomic, it has been estimated to be in the order to 1062 molecules. A structurally diverse and complex compound screening collection, designed to cover a broad area of the chemical space, is of outstanding importance to increase the chances of finding new and better hits outside the limited regions covered by conventional screening libraries.



At PharmEnable we support early drug discovery programs by providing a rapid, cost efficient, and effective platform to identify new hit candidates. At PharmEnable we use our unique and diverse virtual compound library in conjunction with our computational screening programs, to identify novel active chemical starting points against the most challenging biological targets. The discovery of these initial chemical starting points could lead to the development of next-generation medicines, for example, a novel antibacterial agent or a much needed cancer treatment.

Virtual compound library

  • Diverse Library with broad coverage of chemical space
  • Novel and synthesizable compounds
  • Compounds with a high degree of complexity and structural diversity
  • Scalable and dynamic

Computational screening programs

  • Latest Virtual Docking for the identification of novel in silico hits
  • Multi-Target Screening to establish the selectivity and toxicity profiles
  • Machine Learning in Drug Discovery
  • Unlimited to any biological target






We have over 15 years experience in Diversity-Oriented Synthesis (DOS), which aims to efficiently reach and explore broad areas of chemical space. Our world leading experience in computational chemistry enables us to interrogate this repository using state-of-the-art in silico screening programs to identify novel starting points for targets of interest.


Dr. Hannah Sore, Chief Executive Officer

Key roles include: Business strategy and leadership, building customer relations and deal negotiator.
Experience summary: Over 14 years of research expertise, which includes extensive experience within the healthcare and drug discovery sector working in biotechnology, multinational pharmaceutical companies and academia. Over 7 years consulting and business experience across healthcare sectors at Frost & Sullivan and as a founder of HFS Scientific Ltd.


Dr. Natalia Mateu, Chief Scientific Officer

Key roles include: Compound library designer, database manager and medicinal chemistry lead.
Experience summary: Over 10 years of background in organic and medicinal chemistry research, including broad experience in diversity-oriented synthesis of biologically relevant compound collections, target-oriented synthesis of small molecules for drug discovery and several years of expertise in hit-to-lead generation within the pharmaceutical industry.


Lewis Mervin, Head of Technology

Key roles include: Multi-target screening and virtual-screening lead, database and web interface manager.
Experience Summary: Research background in molecular informatics, also known as chem(o)informatics, with expertise in the prediction of properties for small molecules of therapeutic interest (e.g. QSAR and toxicity profiling), including general experience in the analysis of data available in both the biological and chemical domains.


Prof. David Spring, Non-Executive Board and Scientific Avisor

Dave Spring is currently a Professor at the University of Cambridge within the Chemistry Department and a Fellow of Trinity College. He was awarded a Lectureship in 2006, and promoted to a Senior Lectureship in 2008, to a Readership in 2011, and to a Professorship in 2013.

He has over 180 research publications and is a world leader in the area of diversity-oriented synthesis.


Dr. Andreas Bender, Non-Executive Board and Scientific Avisor

Andreas Bender is a Lecturer in Molecular Informatics (also known as Chem(o)informatics) in the Centre for Molecular Sciences Informatics at the University of Cambridge.

In his work, he is focused on the prediction of properties of molecules; here mainly for small molecules (which could be of therapeutic interest), and primarily in the life science field.


For any enquiries please email us:



We have an exciting opportunity for a talented, motivated and dynamic Computational Chemist/Cheminformatician to join the PharmEnable team. We are looking for a scientist passionate about joining an innovative and young company that is changing the way novel therapeutics are discovered by applying state-of-art computational techniques to explore new areas of chemical space.

Main responsibilities

  • To work with and extract information from large chemical data sets
  • To develop, implement, and deliver predictive models critical to the identification of hit compounds
  • To apply CADD methods (ligand-based and structure-based approaches) for the identification of new hit compounds

Required skills

  • PhD in a relevant discipline such as Computational Chemistry, Chemoinformatics, Computational Biology, Bioinformatics
  • CADD experience within a drug discovery environment
  • Basic knowledge of medicinal chemistry to understand drug design and drug discovery projects
  • The ability to work individually as well as in a team
  • Strong oral and written communication, interpersonal, and collaboration skills

Beneficial skills

  • Experience in Scripting or programming language (Python)
  • Knowledge in SMARTS/SMILES coding
  • Experience in structure-based and ligand-based methods (RDkit)
  • Machine learning experience in training, generating and validating models

We offer

  • The ability to work from home anywhere in the world or with our team in Cambridge (UK)
  • A competitive package salary and flexible working hours
  • The chance to join a new dynamic business at an early stage
  • The opportunity to work with drug development companies and partners from all over the world

How to apply? To apply for this position please send an email including your CV and Cover Letter to info@pharmenable.com.

The deadline for receipt of applications is: 19th July 2019