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Top Industry News: April 17-21, 2023
<span data-contrast=”auto”>News Herald (April 21, 2023) </span><span data-ccp-charstyle=”Hyperlink”>Embracing alternatives to animal research while also embracing reality</span> <span data-contrast=”auto”>[While] tremendous strides have been made in creating alternatives, including computer models, organs-on-a-chip, and organoids, which are tissues derived from stem cells to mimic individual organs. These technologies help reduce the number of animals studied. However, we mustn’t forget they are based entirely on the knowledge we have gathered to date. Human-made scientific models are only as good as the data behind them. And when it comes to the incredibly complex functions of health and countless diseases, we have so much to learn. Because of these scientific realities, many experts believe there may always be a need to study animals, at least in some form. Animal activists frequently remind us that mice are not humans. But we also need to recognize that computer models, organoids and organs-on-a-chip aren’t either.</span>
<span data-contrast=”auto”>The Wall Street Journal (April 20, 2023) </span><span data-ccp-charstyle=”Hyperlink”>Biotech Startups Use Models of Human Organs for Drug Discovery</span><span data-ccp-props=”{"201341983":0,"335559740":276}”> </span>
Biotechnology startups are creating tiny models of human organs in an effort to speed the search for novel drugs. By devising more realistic models of human and disease biology, these startups aim to help researchers discover drugs that are more likely to succeed in clinical trials. Today, most compounds entering human studies fail. One reason, proponents of the models say, is that animal studies are often poor predictors of which drugs will work in people.
Fierce Electronics (April 19, 2023) <span data-ccp-charstyle=”Hyperlink”>Generative AI speeds tedious aspects of drug discovery process</span><span data-ccp-props=”{"201341983":0,"335559740":276}”> </span>
The life sciences sector puts years of investment and work into discovering new drugs, and the payoff comes when those drugs can be used to save lives or radically improve patient treatments. While breaking down molecules and analyzing chemical combinations takes time, the most tedious part of this critical process may lie in the production of clinical studies and reports and the regulatory red tape that can prolong the effort. Developing studies, analyzing the results of them, writing up clinical reports, and editing and revising them to address pertinent questions and satisfy legal and regulatory requirements can be a major impediment to the entire process, according to Emmanuel Walckenaer, CEO at Yseop, a French company the develops technology around natural language generation and Generative AI. AI is being brought unto many industries to increase automation, introduce more powerful analytical capabilities, and speed productivity, and while it can be applied directly to the scientific aspects of the drug discovery process, it also can be used to help speed up and improve the accuracy of studies and reports, regulatory applications, and legal filings.
<span data-contrast=”auto”>BBC (April 17, 2023) </span><span data-ccp-charstyle=”Hyperlink”>How artificial intelligence is matching drugs to patients</span>
<span data-contrast=”auto”>A neuroscientist, Dr Cohen Solal is the co-founder and chief executive of Israeli health-tech firm Genetika+. Established in 2018, the company says its technology can best match antidepressants to patients, to avoid unwanted side effects, and make sure that the prescribed drug works as well as possible. “We can characterise the right medication for each patient the first time,” adds Dr Cohen Solal. Genetika+ does this by combining the latest in stem cell technology – the growing of specific human cells – with artificial intelligence (AI) software.</span>
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