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Artificial Intelligence 

Artificial intelligence (AI) is not a new theme, but it has gained considerable momentum during the past decade. AI has already led to groundbreaking success, two examples of which are speech recognition (Siri) and text analysis (Google Translate). The dynamic pace of change in the field of IT and innovation in the field of machine learning have fueled this strong momentum. Using AI in the healthcare industry for drug research and development purposes is particularly interesting and AI-driven projects are underway throughout the drug development process, from preclinical toxicology and pharmacology to clinical trial design and the regulatory approval process, and even in post-approval product launch campaigns. 

Artificial intelligence can be used, for example, to identify the most suitable development candidates more quickly and at less cost. Collaborative interaction between humans and machines is vital here, and a balance must be found between in silico experimentation and in vitro experiments. The objective is to support the efforts of scientists through the use of AI.

Companies large and small are trying to establish a foothold in this business and there is a risk of them rushing into the field without careful forethought. It would be quite sobering, also for investors, if early wins don’t materialize. An additional hurdle big corporations face is that AI is not one of their core business areas, so relatively few resources are allocated to it. Consequently, the top talent in these hybrid areas where computer science and life sciences overlap often elect to work for innovation leaders who are entirely focused on AI and for whom tech expertise is just as important as sound knowledge of biology and medicine. Developing a drug for human use is a complex and highly regulated process, which is why even giant tech companies such as Apple, IBM and Amazon have difficulties entering the fields of digital health and AI in healthcare. When screening investment candidates, BB Biotech AG is mostly interested in companies offering solutions that can alleviate or even completely cure a patient’s ailments; the approach or method used to achieve that is of less importance. BB Biotech is most likely to find such innovation in the US, but China and Europe, the latter led by the UK, have also produced some innovation leaders.

There are two promising AI players in BB Biotech's portfolio. One is Relay Therapeutics, which has access to the world's fastest computer. Researchers use it to run dynamic simulations of known protein structures and identify the smallest of differences. The technology is being used for drug discovery purposes. Black Diamond Therapeutics is the other AI player in BB Biotech's portfolio. It uses machine learning to understand and classify the effects of various mutations on a protein relevant in oncology and then selectively block those mutations with a single agent. BB Biotech itself uses AI in its investment process. “Advanced analytics” plays an important role in its investment decisions. Large sets of data such as EHRs (electronic health records) or health insurance data are mined to provide a better understanding of specific markets from a medical as well as commercial point of view. Tools that help BB Biotech track and process new data inputs and news reports have also been developed to give it a broad and solid understanding of complex topics.

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