WIP1

SAN FRANCISCO--(BUSINESS WIRE)-- Atomwise announced today results from the AIMS (Artificial Intelligence Molecular Screen) initiative that establish the AtomNet AI Platform as a viable alternative to high-throughput screening (HTS) and verify its ability to consistently discover structurally novel chemical matter. The landmark study applied AtomNet to 318 targets through collaborations with over 250 academic labs across 30 countries, representing the largest and most comprehensive virtual HTS campaign reported to date. In a paper published in Nature Scientific Reports, AtomNet successfully identified structurally novel hits for 235 of 318 targets evaluated, representing a significant improvement in hit success rate over traditional HTS. AtomNet demonstrated consistently high hit rates across all target classes, which covered a wide breadth of protein classes relevant across major therapeutic areas, confirming the broad applicability of the AI platform. AtomNet also showed a remarkable ability to discover novel chemical matter, averaging over seven structurally distinct bioactive compounds per target. Developed by Atomwise, AtomNet was the first deep neural network designed to predict the bioactivity of small molecules in structure-based drug discovery. Conventional HTS cannot evaluate over 99% of commercially available molecules, which increasingly come from synthesis-on-demand libraries. In contrast, AtomNet’s virtual HTS approach searches an expanding chemical library of more than 15 quadrillion synthesizable compounds to accurately find hits that deviate from any known binders, enabling rapid discovery from vast, unexplored chemical space. “We need new technologies for new targets. As the pharma industry increasingly moves to tackle harder and harder disease biology, we need new molecules that can address these challenges,” said Mike Varney, former Executive Vice President and Head of Genentech Research and Early Development, and Atomwise Board Member. “For a generation, the pharma industry has largely relied on a single source – HTS – to identify new bioactive compounds. Any new approach needs to demonstrate applicability and robustness across the entire proteome. It is exciting to see Atomwise demonstrate their successes on such a broad range of disease targets.” “The ability of AtomNet to consistently identify novel bioactive chemical compounds solves a fundamental challenge and inefficiency with current small molecule drug discovery,” said Gavin Hirst, Chief Scientific Officer of Atomwise. “Medicinal chemists always want new scaffolds to work on. A new scaffold lets you make progress and potentially unlocks different selectivity, pharmacokinetics, or pharmacodynamics. Access to new scaffolds increases the probability that the developed molecule will meaningfully differentiate in the clinic.” For most projects, the AtomNet training data contained no active molecules for the target protein or any close homologs. As a result, discovered hits often represent first-in-class binders for newly discovered or difficult-to-target proteins. Examples from the AIMS initiative include the first reducer for Miro1, a new target in Parkinson’s disease, the first inhibitors for OTUD7A and OTUD7B, challenging deubiquitinase targets for solid and hematological tumors, and small molecule inhibitors for CTLA-4, a well-established oncology target. “Generally the predictive power of virtual screening platforms has been extremely limited,” said Prof. Gregory Bowman of the University of Pennsylvania, who used AtomNet to uncover a cryptic site for phosphatase PPM1D, a therapeutic target in oncology. “Results of the AIMS study show that AtomNet has a high success rate in finding hits for traditionally challenging biology, like allosteric or protein-protein interactions. This noteworthy ability opens the door for many targets that have been previously deemed intractable.” “AtomNet enabled us to discover highly selective inhibitors for two emerging targets with potential applicability across a range of cancers, but lacking known non-covalent binders,” said Pengda Liu, Ph.D., assistant professor in the Department of Biochemistry and Biophysics at UNC-Chapel Hill. “Despite the novelty and challenge of these targets, the compounds AtomNet predicted are potent to the point where we are currently moving forward with medicinal chemistry efforts. It is clear that AI approaches like AtomNet can fundamentally change the way we think about what is possible, and I have no doubt that it will play a critical role in future drug development.” “We designed AtomNet to be able to extrapolate molecular learnings across targets and actively predict activity for new and challenging targets,” said Abraham Heifets, CEO, Atomwise. “Historically, one of the major challenges for AI-driven discovery has been a need for pre-existing, on-target ligand data to accurately predict activity, narrowing AI’s applicability. We’ve shown for the first time that AtomNet does not require any target-specific training data and can be applied to virtually any target, even those that have been considered undruggable.” “Comprehensively testing the capabilities of AtomNet across such a wide range of targets clearly demonstrates the unprecedented accuracy of the platform to identify novel drug-like scaffolds,” says Izhar Wallach, who led the AIMS initiative and is Chief Technology Officer of Atomwise. “We are hugely thankful for the hundreds of talented researchers across the world who made this collaboration possible.” Atomwise plans to IND application this year for its lead candidate, a novel allosteric TYK2 inhibitor with first-in-class and best-in-class potential, which was discovered using AtomNet. The company’s vision is to invent a better way to discover and develop new medicines to help patients. Our belief is structurally novel chemical matter increases the likelihood of developing first-in-class and best-in-class medicines that have the potential to transform patient care. About Atomwise Atomwise is a TechBio company leveraging AI/ML to revolutionize small molecule drug discovery. The Atomwise team invented the use of deep learning for structure-based drug design, a core technology of Atomwise’s best-in-class AI discovery and optimization engine, which is differentiated by its ability to find and optimize novel chemical matter. Atomwise has extensively verified its discovery engine, having demonstrated the ability to find compounds with therapeutic potential hundreds of times across a wide variety of protein types and multiple “hard to drug” targets. Atomwise is advancing a proprietary pipeline of small-molecule drug candidates. Our vision is to invent a better way to discover and develop new medicines to help patients. Learn more at atomwise.com or follow @AtomwiseInc.

Bayer, PMV Pharma, and Ikena Oncology have all announced staff cuts as a result of strategic restructurings. Credit: Andrii Yalanskyi/Shutterstock.com Amidst a successful conclusion to the 2024 JP Morgan Healthcare Conference, biotech and pharma layoff numbers are on a consistent rise with PMV Pharmaceuticals and Ikena Oncology being the latest to follow pharma giant Bayer ’s recent restructuring plans. PMV Pharmaceuticals plans to fire 30% of its workforce in a bid to free capital that will go towards the development of its lead tumour agnostic therapy PC14586. As per the New Jersey-based company, the strategic restructuring will extend PMV’s cash runway until the end of 2026 and will allow the company to focus on discovery research efforts and prioritise initiation of a Phase II clinical study of p53 reactivator PC14586 that is slotted for commencement in Q1 2024. The precision oncology company’s latest restructuring follows a March 2023 pipeline optimisation effort, in which the company announced that its WIP-1 inhibitor and R273H mutation-targeting programs had been shelved to drive the development of its lead candidate. Also riding the layoff wave is Bayer, which recently unveiled a new operating model called “Dynamic Shared Ownership” (DSO) which will see “significant staff reductions” as a result of the newly implemented regulations. The company plans to begin job cuts in the coming months and expects to conclude the process by the end of 2025. “Our new operating model is designed to make Bayer faster and more innovative. However, its introduction will come at the expense of many managerial employees,” Dr. Barbara Gansewendt, Chairwoman of the Bayer AG Group Executives’ Committee said in a 17 January press release. The pharma giant did not provide a quantifiable scale of the impending layoffs. On 18 January, Ikena Oncology also revealed that it will jettison 35% of its workforce in in order to prioritise resources for its clinical stage cancer programs, IK-930 and IK-595. The company anticipates completing the restructuring by 31 March 2024.

New research illuminates the mechanisms at work that prevent the p53 gene from triggering effective cancer cell death. Cancer is a disease driven by gene mutations. These mutated genes in cancer fall into two major categories: tumor suppressors and oncogenes. Mutations in tumor suppressor genes can allow tumors to grow unchecked -- a case of no brakes -- while mutations in oncogenes can activate cell proliferation, pushing the gas pedal all the way to the floor. Researchers studying mutations in tumor suppressor genes have dedicated significant focus to p53, the most frequently mutated tumor suppressor gene in human cancers. Over the past two decades, much effort has been devoted to designing biologically targeted therapies that specifically activate p53. However, while research has shown that these therapies are effective at inducing p53 activity, they generally can't kill cancer cells. As observed for other biologically targeted therapies, activation of p53 has been shown to stop tumor growth for a period of time, but the cells eventually mutate and become resistant to treatment. New research by University of Colorado Cancer Center scientists illuminates the mechanisms at work that prevent p53 activation from triggering effective cancer cell death. They show that inhibiting two distinct repressors of p53 can elicit cancer cell death through activation of a complementary gene network known as the Integrated Stress Response. "When you block both the major p53 repressor, known as MDM2, and its minor repressor, known as PPM1D, p53 works much better in terms of inducing cancer cell death, and this enhanced killing activity requires the Integrated Stress Response" explains Joaquin Espinosa, PhD, a professor of pharmacology in the CU School of Medicine, director of the Linda Crnic Institute for Down syndrome, and senior author of the study. "This is an important step in making p53-based biologically targeted therapies more effective." Inducing cancer cell death This development is an important milestone in almost two decades of research conducted by Zdenek Andrysik, PhD, an assistant research professor of pharmacology in the CU School of Medicine, and other members of the Espinosa lab. Their and other research has worked to understand the role of MDM2 and PPM1D, two proteins that repress p53 inside tumor cells, and the mechanisms by which inhibiting them leads to cancer cell death. "It was already established that MDM2 is a major repressor and PPM1D is a minor one," Espinosa explains. "For a long time, the hope was that inhibiting just the major repressor would suffice. Much effort was invested in developing small molecules that block MDM2, millions of dollars were spent, but these drugs performed poorly in clinical trials." Researchers then turned to minor repressors, including PPM1D. "A lot less is known about PPM1D and other minor repressors of p53," Andrysik says, "but it soon became clear that if you inhibit both MDM2 and PPM1D, p53 can effectively induce cancer cell death. However, the underlying mechanisms driving this synergy were unknown." Understanding the mechanisms Espinosa and Andrysik have been able to demonstrate that inhibiting MDM2 and PPM1D activates the Integrated Stress Response, which is a signaling pathway that stimulates a protein called ATF4. They further demonstrated that ATF4 partners with p53, working together to cause cancer cell death. Inhibiting MDM2 and PPM1D, and thus allowing p53 to partner with ATF4 in taking cancer cells to death, has shown promise for multiple cancer types in the laboratory, Andrysik says. This mechanistic insight quickly revealed additional pharmacological strategies to induce cancer cell death. For example, Andrysik and Espinosa repurposed the drug Nelfinavir, which originally was approved as an HIV therapy. "Now we know that Nelfinavir activates the Integrated Stress Response, thus becoming a great combination with MDM2 inhibitors," Espinosa says. Andrysik and Espinosa are continuing their research to understand more about mechanisms of the synergistic response that happens when MDM2 and PPM1D are inhibited and p53 is activated. "Our data indicates that cancer cells are particularly vulnerable to this dual activation of p53 and the Integrated Stress Response, which may offer a therapeutic window in the clinic, sparing normal cells from the killing effects of p53," Andrysik says. Espinosa adds that "a holy grail of cancer research has been the restoration of p53 activity to induce tumor regression. For the past 20, 30 years, a lot of research efforts have been devoted to finding more elegant solutions to broadly acting chemotherapy or radiation. As we learn more about the genes and proteins mutated in cancer, we're more able to see when the brakes are failing and restore them, or when the gas pedal is all the way to the floor and lift it with specifically targeted inhibitors."