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Pharma Tech Outlook | Monday, July 18, 2022
Pharmaceutical Technology takes a look at some of the tech innovations set to impact drug discovery and development in 2022.
FREMONT, CA: According to a GlobalData survey conducted this year, more than 70 per cent of pharma industry respondents believe that smart technology implementation will have the greatest impact on drug development. As the year comes to a close, pharmaceutical technology examines some of the technological innovations and approaches that have the potential to transform drug research in 2022. Supercomputers outperform general-purpose computers in terms of speed and performance, and they are especially useful for performing scientific and data-intensive tasks. It stands to reason, then, that researchers are attempting to apply supercomputing to the time-consuming process of drug discovery and design.
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Molecular simulations help to model target and drug interactions completely in silico, which speeds up drug discovery by millions of times. The discoveries of AlphaFold and RoseTTAFold, which resulted in a thousand-fold increase in known protein structures, and AI, which can generate a thousand more potential chemical compounds, have multiplied the opportunity to discover drugs by a million. There are over ten thousand diseases that do not have treatment. Whether it is to discover drugs or treat patients, multiple sources of health data must be used. Multimodal artificial intelligence will take us to a new frontier in discovering disease pathways and personalising patient treatment and prognosis by leveraging the world's largest data sources. To assist application developers in industrialising their AI technology and expanding the application's business benefit, artificial intelligence must be trained and validated on data that resides outside the possession of their group, institution, and geography. Federated learning is critical for facilitating such collaboration to build and validate robust AI models without sharing sensitive data. Federated learning will be a critical capability for facilitating AI's continuous learning and evaluation.
Gene editing, which involves inserting, deleting, modifying, or replacing DNA in a genome, is a promising and relatively new approach to treating genetic disorders. Even more recent is the concept of gene editing to combat inherited diseases. This technique involves writing therapeutic messages directly into the genome to correct disease-causing genetic errors - and the company claims the technology has the potential to target virtually any inherited disorder at its root. Mobile genetic elements (MGEs), a type of genetic material that can be inserted into specific locations within a genome using DNA or RNA templates, are used in gene writing.
Computational methods for drug discovery are not new, but using ultra-efficient quantum computers to discover previously unknown compounds has only recently emerged as a promising area. While traditional computers use "bits" that are either on or off, quantum computers use "qubits" that can be on, off or both–a phenomenon known as superposition. This superposition property enables quantum computers to significantly accelerate and optimise testing and predictions, making the technology particularly promising for drug discovery efforts. The demonstration of quantum utility, defined as a quantum system outperforming classical processors of comparable size, weight, and power in similar environments, could be useful in the development of new materials and medicines.
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