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Interview with Joachim Coenen: Big data and AI in animal research

Big data and artificial intelligence will play a key role in advancing the 3Rs principle in preclinical research. In this interview, Joachim Coenen, Senior Expert Animal Science and Welfare at the Merck Group, describes the state of play and offers an outlook on the direction developments should take.

1. Interview with Dr. Joachim Coenen

How important are platforms and collaborations to make data from preclinical research, including with animals, accessible and usable for researchers with a view to promoting the 3Rs – reduce, replace and refine? 

Joachim Coenen: To promote the 3R principle, we need to create platforms and collaborations that make data from preclinical research accessible and usable for researchers. This has several benefits. It allows the reuse and further development of existing data and models, thus reducing the number of laboratory animals required. At the same time, platforms and collaborations facilitate the exchange of knowledge and experience via “refine” or “replace” methods. Refine methods, which include human endpoints, analgesia or micro-CT, help to improve animal welfare. Replace methods involve developing and validating alternative methods, such as in-vitro systems or computer models, to replace all or some animal experiments.

Can you give us examples of such platforms and collaborations in practice?

A good example is the DZHK Heart Bank of the German Center for Cardiovascular Research (DZHK), where data and biosamples from preclinical cardiovascular research are collected and made available to researchers worldwide. The work of the DFG research group FOR 2591 is another good example. The research consortium works on the issue of severity assessment in animal-based research. Ideally, however, an artificial intelligence (AI) is created that develops a complete preclinical and clinical program under the control of researchers. All available data and methods are used as a basis for developing such a program. This can include new approach methods (NAMs), but also animal experiments where necessary. Such an AI-based platform proposes studies to the researchers, and based on the results of these studies, the program is then adapted and applied all the way through to creation of the approval documents (e.g. IND or CTDs).

That sounds very complex. What are the prerequisites for implementing such an AI-driven platform for preclinical research?

It goes without saying that some parameters need to be clarified for such projects. This includes compliance with standards for the collection, processing, storage and publication of data. Moreover, data protection, data security and the question of intellectual property have to be handled. But the willingness of researchers to collaborate and exchange data and resources with each other is certainly also a key factor. Last but not least, of course, is the availability of financial, technical and human resources. Preclinical research is an essential step in the development of new drugs and therapies that can improve the lives of patients. However, it requires significant investment and time, as well as compliance with ethical and legal standards.

What are the chances of big data and AI making headway in Switzerland as well?

This question was actually answered in August 2023 by Handelsblatt Inside (Digital Health) in an article entitled “Novartis leading user of AI in pharmaceutical research.” According to an analysis by the Center for International Economics and Business and International Trade and European Integration (CIEB), Novartis is the leading user of AI because three percent of all articles published by Novartis in the scientific database Scopus deal with AI in drug development. Roche uses AI, to my knowledge, primarily in the fields of oncology, immunology, infectious diseases and neurology. Examples of specific applications of AI at Roche include AI-powered analysis of computed tomography images of the lungs to diagnose COVID-19 infections more quickly and accurately, AI-based analysis of genetic data to identify rare diseases and find appropriate treatments, andAI-powered tumor research to discover new biomarkers and agents. Roche is thus also a leader in the use of AI in medicine. There is therefore a very good chance that progress will be made on this front in Switzerland.

Are there specific reasons for this?

Switzerland is a country with a high level of research and a strong commitment to animal welfare, but without disregarding the necessity of animal experiments. I have always found the research community in Switzerland to be progressive and data-driven, pragmatic and responsible. In my view, Switzerland offers an optimal combination for the development of AI-based systems for pharmaceutical research, and it already has a number of organizations that can provide valuable support for such a project.

What organizations are you referring to?

These are the Swiss 3R Competence Center (3RCC), which promotes and coordinates implementation of the 3R principle, the Swiss Platform for Advanced Scientific Computing (PASC), which facilitates access to high-performance computers for preclinical research, the Swiss Biobanking Platform (SBP), which improves the quality and availability of bio-samples for preclinical research, and the Swiss Clinical Trial Organization (SCTO), which supports collaboration between clinical and preclinical researchers. These platforms and collaborations enable researchers to benefit from synergies, knowledge transfer and resource sharing. They also help to increase the visibility and recognition of preclinical research in Switzerland. I think that these initiatives are a good example for other countries interested in the issue.

“Such an AI-based platform proposes studies to the researchers, and based on the results of these studies, the program is then adapted and applied all the way through the creation of the approval documents.”

Joachim Coenen

And what role do pharmaceutical companies play?

The participation of Swiss pharmaceutical companies in the development of big data and AI-driven platforms and collaborations is essential for developing and using data from preclinical research. This is the only way for AI and science to be used pragmatically to conduct studies and generate data that can meet the requirements and rigorous controls of regulatory authorities worldwide.

Who do you see in the role of promoter or initiator of such platforms?

In pharmaceutical development, I see the Swiss pharmaceutical companies taking the lead. They know exactly where AI can best be used to successfully develop their drugs. However, they also know where there are gaps and where there is still a need to work with conventional (possibly animal-based) methods. However, the regulatory authorities must also be involved in these projects from the outset, as they are the ones ultimately approving a drug based on the data produced. The role of coordinator could be played by the 3R Competence Center mentioned above. However, it must be clearly stipulated that the pharmaceutical industry is in the lead and steering the project.

And the role of researchers?

Such projects can only be successful if scientists from different disciplines, who often do not have much to do with each other, are involved. They can come from anywhere. From industry, academia or the start-up scene, anyone who can dedicate themselves to a specific project.

2. Profile of Dr. Joachim Coenen

About the interviewee

Dr. med. vet. Joachim Coenen is Senior Expert Animal Science and Welfare at the Merck Group (EMD in the USA and Canada) and works in SQ-A (Corporate Animal Affairs) at the Merck Group. Dr. Coenen graduated as a veterinarian and obtained his doctorate in biochemistry and endocrinology from the University of Giessen in Germany. He is a specialist veterinarian for experimental animal science and certified as a Diplomate of the American Board of Toxicology (DABT). In addition to his experience in animal science and animal welfare, he has more than 15 years of experience in non-clinical drug development, licensing and outsourcing and has worked in the German and US pharmaceutical industries. Among many other activities in national and international associations (EFPIA, vfa), he serves as Council Chair of the SET Foundation and is Chair of the Animal Welfare Working Group of Interpharma – the association of Switzerland’s research-based pharmaceutical industry, currently serving as Immediate Past Chair on the Board of Directors of AAALAC International and member of the Federal Commission for Animal Welfare at the German Federal Ministry of Food and Agriculture.