Insilico Medicine uses AI to uncover preclinical candidate for kidney fibrosis

By Jenni Spinner contact

- Last updated on GMT

(Mohammed Haneefa Nizamudeen/iStock via Getty Images Plus)
(Mohammed Haneefa Nizamudeen/iStock via Getty Images Plus)

Related tags: Insilico Medicine, preclinical development, kidney disease, kidney failure, Drug discovery, Artificial intelligence

The drug discovery company reportedly used AI-powered drug discovery to come up with a promising preclinical candidate for treatment of the kidney ailment.

Insilico Medicine, a company that uses advanced machine learning (ML) technology to discover and develop novel therapies, reports it has used its artificial intelligence (AI) powered discovery platform to deliver a preclinical candidate for the treatment of kidney fibrosis.

Alex Zhavoronkov, CEO and founder of Insilico Medicine, said the discovery could be positive news to the millions of people around the globe suffering from kidney disease.

Chronic kidney disease affects 10% of the world’s population, and, unfortunately, it has no cures or efficacious drugs on the market​,” he said. “Kidney fibrosis is the common pathogenesis in the progression of chronic kidney disease and is a major unmet medical need; approximately 850m people worldwide (almost a billion) have kidney disease often being driven by or associated with kidney fibrosis.”

According to the US Centers for Disease Control (CDC), it is estimated that more than 1 in 7 (15% of US adults, or 37m people) live with chronic kidney disease. The pervasive ailment leads to the gradual loss of kidney function over an extended period, ranging from several months to several years.

Kidney fibrosis is the final common pathway of a wide variety of chronic kidney diseases, Prior to the US Food and Drug Administration’s (FDA’S) approval of dapaglifozin, there had not been any approved treatment of chronic kidney disease available to patients; instead, treatment of diabetic and hypertensive kidney damage had aimed at controlling glucose levels and blood pressure, respectively, with other renal diseases and injuries treated empirically with anti-inflammatory and/or immune-suppressive drugs.

While the approval of dapaglifozin (originally is an anti-diabetic drug) gives chronic kidney disease patients a new treatment option, individuals dealing with autoimmune-related forms of chronic kidney disease were excluded from the study and are not expected to benefit from the drug. For the latter grouping of chronic kidney disease patients, Insilico Medicine’s drug candidate could represent a breakthrough; what’s more, other patients unable to tolerate dapaglifozin due to side effects also could benefit from an alternative.

According to Insilico Medicine, this preclinical candidate has demonstrated desirable pharmacological properties and pharmacokinetic profile and has demonstrated highly promising results in in-vitro and in-vivo preclinical studies. The company reports it is working to advance the therapy to clinical trials, with plans to complete investigational new drug (IND) enabling studies in 2022.

OSP_InsilicoKidney_AZ
Alex Zhavoronkov, CEO and founder, Insilico Medicine

We are very excited to see that our AI-powered drug discovery engine has managed to uncover novel targets and novel molecules that have demonstrated preclinical efficacy in kidney fibrosis​,” said Zhavoronkov. “We also used our InClinico engine to produce the actuarial models for the multiple diseases driven by kidney fibrosis, and are very excited about the clinical prospects of this program​.”

In February 2021, Insilico Medicine reported a “breakthrough” achievement with the announcement that its AI technology successfully identified a novel drug target and compound to treat idiopathic pulmonary fibrosis (IPF), another fibrotic disease affecting patients with high unmet medical needs.

The company reportedly achieved the identification in under 18 months, with a budget of $2.6m USD.

Then, the company announced it leveraged its PandaOmics platform to develop the target hypothesis for kidney fibrosis and used Chemistry42 to generate compounds with drug-like properties. According to the team, the compound markedly inhibited the development of fibrosis and significantly improved myofibroblast activation, critical for tissue repair and wound healing.

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