Preclinical candidate to target ENPP1 for cancer immunotherapy and the treatment of rare disease using generative AI

19 May 2023
Preclinical candidate to target ENPP1 for cancer immunotherapy and the treatment of rare disease using generative AI

An AI-driven drug discovery company has announced a potentially best-in-class preclinical candidate targeting ENPP1 for cancer immunotherapy and the potential treatment of Hypophosphatasia (HPP).

ENPP1 is an ecto-nucleotide pyrophosphatase that plays an important role in purinergic signalling that regulates immune, cardiovascular, neurological, and haematological system functions.

Elevated ENPP1 expression is associated with metastasis and poor prognosis in multiple tumour types. ENPP1 inhibition enhances the antitumor effect of the host immune system by regulating extracellular cGAMP levels to activate the cGAS-STING pathway.

In addition, the inhibition of ENPP1 has proven to reduce the production of pyrophosphate (PPi) and re-establish mineralisation through restoring the balance of PPi and phosphate(Pi).

This is expected to be an available strategy to develop small molecule therapies for Hypophosphatasia (HPP), a rare genetic disorder characterised by abnormal development of the bones and teeth.

ISM5939, from Insilico Medicine, is an orally available inhibitor of ENPP1 with a distinctly novel molecular structure, designed with the assistance of Insilico’s generative AI drug design engine, Chemistry42.

The compound demonstrates robust antitumor efficacy in in vivo studies.

It also shows a favourable safety profile, as well as in vitro ADMET and in vivo pharmacokinetic profiles, which expects to improve clinical compliance with QD (quaque die) dosing frequency.

Insilico will further explore the in vivo efficacy of the candidate in HPP models and initiate an Investigational New Drug (IND)-enabling study to advance the candidate to clinical stage.

Powered by AI-driven drug discovery engines and computer-aided drug design methods, Insilico obtained the lead compound of this program within 3 months of project initiation.

Insilico’s medicinal chemists further optimised the lead compound and solved the CYP self-induction of the compound through structural modifications to ensure steady state of oral drug exposure during continuous dosing.

The molecule was nominated as a preclinical candidate compound in April 2023.

“ISM5919 is a novel molecule whose structure differs significantly from that of published patents. It once again displays the ability of generative AI to design molecules from scratch,” said Feng Ren, PhD, Co-CEO and Chief Scientific Officer of Insilico Medicine.

“ENPP1 is a potential immuno-oncology target that has received widespread attention, but the development of new therapies targeting ENPP1 has been relatively slow. We are committed to evaluating the candidate with full speed to provide an innovative solution for cancer immunotherapy.”

“With the accumulation of years of data, and increasing sophistication of generative AI technologies, we have been able to discover targets and develop new promising therapeutics at a remarkable pace,” says Insilico Medicine founder and CEO Alex Zhavoronkov, PhD. “We’re looking forward to advancing this latest cancer immunotherapy drug, which works on the promising target ENPP1, to IND-enabling studies.” 

Source: Insilico Medicine