REDMOND, WA, June 03, 2021 – Pattern Computer® Inc. is pleased to announce that the recently completed testing of a novel and newly developed candidate treatment for triple negative breast cancers has shown statistically significant positive results.

The Pattern Computer team has developed a unique process in computational biology for discovering the genetic causes of a range of cancers, and is using this system to design new treatment regimens comprised of known drugs and therapies. The Pattern Discovery Engine™ (PDE) from PCI enables high- performance, distributed, heterogeneous computing, and exponential increases in complexity of analyzing multiple gene-level interactions and conditions that lead to a wide range of cancers.

A prime objective of this Pattern Computer project is to discover the complex origin conditions and drivers behind the genesis of triple-negative breast cancers (TNBC). If successful, this could allow the discovery of effective treatments that could in turn be quickly and safely brought to clinical testing, and to the market. This subclass of breast cancer was chosen for its current dearth of targeted treatments. The ultimate goal of the PCI team is to reduce costs of treatments, increase the number of people who can be treated, to improve the standard of care, and to save lives.

“Using off-the shelf, FDA-approved drugs dramatically decreases the cost and time to market of our solutions. National Lab testing has already validated that the drug cocktails we have designed address the interactive nature of the gene pathways we are seeing; in vitro, we can kill TNBC cells with little or no harm to healthy cells. The current report on our first cocktail candidate indicates that these drugs can work effectively together in select doses in mice. This type of approach may provide a major step forward in addressing a number of the devastating diseases afflicting people today,” said Mark R. Anderson, CEO of Pattern Computer.

The Pattern Computer team discovered a large new constellation of genes correlated with the breast cancers being studied, using PCI’s PDE. The team then leveraged the PDE to analytically design 17 different new candidate cocktail treatments. Initial testing was done in organoids at Lawrence Berkeley National Laboratory, winnowing the candidates list to two cocktails. The process was then moved to a world class private laboratory, where statistically significant positive results were achieved in animal tests.

“Pattern has developed a new methodology for discovering and exploiting important pathways in tumors to design novel, precisely targeted therapeutic cocktails. Making use of published datasets in conjunction with a proprietary knowledgebase on approved drugs, Pattern has identified combination therapies that, in preclinical trials, have shown efficacy against models of recalcitrant tumor types, and have demonstrated remarkable safety profiles. Pattern’s innovative and unique approach to AI-driven computational biology stands to significantly reduce the time to market of novel cancer therapies, to improve the quality of life relative to chemotherapeutic treatments, and, ultimately, to save lives,” said Prof. J. Ben Brown (UC Berkeley & Lawrence Berkeley National Laboratory).

The testing process will continue, evaluating the safety and efficacy of this new treatment at varying dosage amounts and durations. A second, different PDE-derived cocktail for the same disease is still in animal testing.

PCI is currently using the PDE to obtain results in breast, prostate, ovarian, lung, and colorectal cancers, with other diseases in process. One of the primary goals of the Pattern Computer team is to reduce the time and high costs required to analyze the origin conditions that allow the growth of cancers, and then to develop novel treatment options in days or weeks, rather than in years. The world has recently seen impressive reductions in time to market for life-saving vaccines, and PCI is driving this same type of step change in applying new computing and analytical techniques to solving some of the most vexing problems in the areas of genetic oncology.

The foregoing contains statements about the Pattern Computer’s future that are not statements of historical fact. These statements are “forward looking statements” for purposes of applicable securities laws, and are based on current information and/or management’s good faith belief as to future events. The words “believe,” “expect,” “anticipate,” “project,” “should,” “could,” “will,” and similar expressions signify forward-looking statements. Forward-looking statements should not be read as a guarantee of future performance. By their nature, forward-looking statements involve inherent risk and uncertainties, which change over time, and actual performance could differ materially from that anticipated by any forward-looking statements. Pattern Computer undertakes no obligation to update or revise any forward-looking statement.  

About Pattern Computer

Pattern Computer, a Seattle-area startup, uses its proprietary Pattern Discovery Engine to solve the most important and most intractable problems in business and medicine. Its proprietary mathematical techniques can find complex patterns in very-high-order data that have eluded detection by much larger systems.

While the company is currently applying its computational platform to the challenging field of drug discovery, it is also making pattern discoveries for partners in several other sectors, including additional biomedical research, materials science, aerospace manufacturing, veterinary medicine, air traffic operations, and finance.

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