First Generative AI Drug Begins Phase II Trials with Patients
New Milestone in AI Drug Discovery:
Insilico Medicine has achieved a new milestone in artificial intelligence drug discovery – bringing the first drug discovered and designed by generative AI into Phase II clinical trials with patients. This lead program, for a potentially first-in-class pan-fibrotic inhibitor known as INS018_055 - is Insilico's moonshot drug – one that demonstrates beyond a doubt the validity of Insilico's end-to-end AI drug discovery platform, Pharma.AI.

Idiopathic pulmonary fibrosis (IPF) is a rare lung disease characterized by chronic scarring of the lungs and progressive and irreversible decline in lung function. It affects approximately five million people worldwide, there are few treatments available, and patients typically die 2-5 years following diagnosis. A drug to treat IPF needs to meet the most rigorous safety requirements because patients will take it for the rest of their lives.

Insilico chose to target IPF because the Company wanted this lead program to set a precedent: simultaneous success in target discovery and drug candidate generation for a broad indication such as fibrosis, and a historical proof of concept for the ability of deep learning to link biology and chemistry in an integral workflow.
With demonstrated potential against both fibrosis and inflammation, INS018_055 could offer another option for patients worldwide.
The achievement of the first dose for INS018_055 in the Phase II clinical trial is not only an important step for Insilico, but also a milestone for AI-driven drug discovery and development. Together, we are expecting more achievements powered by AI for global unmet medical needs.
Feng Ren, PhD
co-CEO and Chief Scientific Officer of Insilico Medicine
Speeding new treatments with generative AI
The journey of INS018_055 to Phase II trials has been one of continual "firsts." The preclinical candidate was selected in Feb. 2021, just 18 months after the project began. Nine months later the Company announced first-in-human for Phase 1 trials. It was a milestone in drug discovery – from novel target discovery to Phase 1 in under 30 months, about half the time the process would take with traditional drug discovery, thanks to the speed and efficiency provided by AI, and for a fraction of the cost.

To build the initial hypothesis, Insilico scientists trained the target discovery engine PandaOmics on a collection of omics and clinical datasets related to tissue fibrosis, annotated by age and sex. PandaOmics performed sophisticated gene and pathway scoring and found relevant targets via deep feature synthesis, causality inference, and de novo pathway reconstruction. The target novelty and disease association scoring was assessed by a natural language processing (NLP) engine, which analyzes data from millions of data files, including patents, research publications, grants, and databases of clinical trials. PandaOmics revealed 20 targets for validation, and one novel intracellular target – "Target X" – was prioritized for further analysis.

Next, scientists applied Chemistry42, the generative AI chemistry engine, to this novel target. The engine uses 500 predictive pre-trained models, including transformer-based, GANs and genetic algorithms, which reward and punish generated molecules based on how well they meet the necessary conditions – including hitting the target, metabolic stability, and penetrability. Ultimately, scientists selected 79 molecules to synthesize. They chose the 55th molecule which showed promise in improving fibrosis and good safety profile in mouse models.
Bringing efficiency to drug discovery,
and hope to IPF patients
Idiopathic Pulmonary Fibrosis is a broad medical condition that is limited to the lungs and primarily affects older adults. As the disease progresses, the health of the patient gradually deteriorates leading to potentially life-threatening pulmonary failure. Currently, very few therapies are available to patients, providing limited options to fight the disease.

The series of novel small molecules generated by Chemistry42 showed promising results on target inhibition. One particular hit demonstrated activity with nanomolar (nM) IC50 values. When optimizing ISM001, scientists achieved increased solubility, good ADME properties, and a favorable CYP inhibition profile, while retaining nanomolar potency. Interestingly, the optimized compounds also showed nanomolar potency against nine other fibrosis-related targets.

In follow-up in vivo studies, the molecules showed activity improving fibrosis in a Bleomycin-induced mouse lung fibrosis model, leading to further improvement in lung function. These compounds also demonstrated a good safety profile in a 14-day repeated mouse dose range-finding (DRF) study.

The best-performing molecule was nominated as a preclinical drug candidate in December 2020 for IND-enabling studies. A final version of the drug candidate, INS018_055, demonstrated highly promising results in multiple preclinical studies including in vitro biological studies, pharmacokinetic and safety studies. The compound improved myofibroblast activation, a contributor to the development of fibrosis. NS018_055's target is novel and has potential relevance in a broad range of fibrotic indications.
Testing the first generative AI drug
in human trials
After completing IND-enabling studies, Insilico initiated a first-in-human microdose trial of INS018_055 in November 2021, conducted in Australia in 8 healthy volunteers. The results exceeded expectations with a favorable pharmacokinetic and safety profile of the drug in humans which successfully demonstrated clinical proof-of-concept.

The novel small molecule inhibitor advanced to Phase I clinical trials, in which 78 healthy volunteers in New Zealand were enrolled in 10 cohorts consisting of 5 single ascending dose and 5 multiple ascending dose cohorts to determine maximum tolerated dose and establish dosage recommendations for future Phase II studies.
To my knowledge, this is the first program where the target is discovered using AI, modulating a broad biological process like fibrosis, the molecule is designed using AI, targeting a chronic disease with a large addressable market to enter Phase I clinical trials. It is a very exciting time for end-to-end AI-powered drug discovery.
Feng Ren, PhD
co-CEO and Chief Scientific Officer of Insilico Medicine
In January 2023, Insilico had achieved positive topline results from its Phase I studies – with INS018_055 found to be safe, and well tolerated by volunteers, with no significant accumulation after 7 days and exhibited a favorable PK profile. These results, along with Orphan Drug Designation by the FDA in February 2023, paved the way for the first Phase II trials for the first fully generative AI drug.

With the safety of its lead drug candidate for IPF established, Insilico launched Phase II trials with patients in China and the U.S., dosing the first patients in June 2023. The study is a randomized, double-blind, placebo-controlled trial to assess the safety, tolerability, pharmacokinetics and preliminary efficacy of 12-week oral INS018_055 dosage in subjects with IPF divided into four parallel cohorts. The Company will expand the patient population to 60 subjects with IPF at about 40 sites in both the U.S and China.

The launch of Phase II trials for the first AI-discovered and AI-designed drug represents a milestone for the Company and the industry as a whole – and offers hope to IPF patients and others who are awaiting new cures.
When we started developing generative AI for drug discovery, I never expected to see the clinical and preclinical results we have today. Initiating Phase II trials with this novel inhibitor for IPF represents a major milestone for deep generative reinforcement learning in drug discovery. We will explore the efficacy for patients of AI-discovered and designed treatments in clinical trials, which is a true validation of our generative AI platform. We are eager to continue to advance this potentially first-in-class therapy forward to help patients in need and show the value of generative AI in drug discovery and development.
Alex Zhavoronkov, Ph.D.
Founder and CEO of Insilico Medicine
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