Qureight's synthetic study arms validate clinical efficacy in pioneering rare lung disease treatment

Qureight, a deep-learning analytics company accelerating drug development through AI-powered data curation, today announced that its digitally-twinned synthetic control arm has been used in a breakthrough clinical trial application in place of a human placebo group, marking a world-first in lung disease research. The study, presented at the American Thoracic Society, demonstrates significant clinical efficacy for Avalyn's inhaled pirfenidone (AP01), a promising treatment for idiopathic pulmonary fibrosis (IPF), a rare and high-mortality lung disease.

Powering clinical study designs to meet challenging registrational endpoints requires large patient cohorts, meaning studies can take multiple years to complete, even in early-stage efficacy trials. This places a significant burden on drug developers in a field where new therapies are urgently needed. Synthetic study arms are a novel but highly attractive concept to reduce trial size, duration and cost, and accelerate potential new therapies to patients. The ability to identify placebo or control arm patients who are digitally-twinned with treated subjects - especially using processes incorporating both clinical data and quantitative image analytics - offers the possibility to create randomized placebo and control arms containing patients with more closely matched disease states. However, this approach has not been previously possible.

Qureight has collated an extensive biorepository of historic IPF patient clinical and lung image data, stored within its proprietary deep-learning platform. Treated patient groups from clinical trials can be digitally paired to synthetic control groups generated by Qureight, using measures of clinical significance and baseline disease extent. Simulating disease progression differences between such closely matched patient groups may increase accuracy in endpoint assessment. Patient groups with highly comparable baseline disease states would be expected to progress similarly, allowing more precise assessments of treatment effects than relying on randomized placebo comparisons, reducing the need for human placebo recruitment. This novel approach is particularly impactful for trials in orphan diseases such as IPF, where patients can be smaller in number and unresponsive to standard of care. Access to experimental therapies can extend life, making placebo arms less ethical.

The recently-published study assessed data from a study of an investigational therapy from Avalyn, an optimized inhaled formulation of pirfenidone for the treatment of IPF. By matching AP01-treated patients to real-world, treatment-naïve IPF patients within the Qureight platform, filtering first by clinical trial inclusion criteria, then applying proprietary AI-based quantitative image analytics, the Company generated a tightly matched synthetic control pool. From this pool, over 10,000 randomly sampled control groups were created and the top 1,000 that best-matched with the treatment group were evaluated for comparative efficacy testing. Results showed a statistically-significant reduction in lung capacity (FVC) over the 48-week treatment period compared to the 100mg dose of AP01, suggesting significant treatment effect.

The launch of Qureight's Synthetic Study Arms is a watershed moment for clinical research in lung diseases. By creating an ethical, image-driven synthetic control arm, we can accelerate trial timelines, reduce costs and, most importantly, spare patients from unnecessary placebo assignments. At this stage, we are evaluating the wider applications of the platform across broader standards of care with our partners. This innovation not only underscores our commitment to transforming trial design but also paves the way for a new era of data-driven therapeutics."

Dr Muhunthan Thillai, CEO, Qureight

Howard M. Lazarus, MD, FCCP, and CMO of Avalyn, said: "Qureight's work helps to validate AP01's treatment effects in IPF patients and has the potential to reshape how we think about and design future studies to help us develop improved treatments and standard of care that patients so urgently need."