Quotient Sciences Proprietary AI-Enhanced Solution Optimizes Formulation in Clinical Study
— Proprietary algorithm optimized tablet composition and dose level for clinical study in healthy participants —
— Interim results suggest significant potential for developing optimized formulations with fewer clinical rounds —
The algorithm reached the study's preset pharmacokinetic target within three dosing periods, meeting the program's interim objectives.
Developing a formulation that achieves a target pharmacokinetic profile conventionally requires multiple rounds of formulation development and clinical testing, taking months or years to complete. "Predicting how a modified-release tablet will behave in humans is difficult," said
The clinical work follows laboratory screening in which the same algorithm demonstrated that it could rapidly learn the relationship between tablet composition and in vitro drug release. The algorithm mapped the formulation design space after screening one-third fewer formulations than conventional methods. That finding prompted the hypothesis now being tested in the clinic: A model capable of learning that relationship in the laboratory could also learn how composition influences pharmacokinetics in humans.
The algorithm entered the trial trained only on in vitro release data. After each dosing period, it was retrained on tablet dissolution results and pharmacokinetic data from the healthy participants, then asked to select the next composition and dose. Quotient Sciences set the limits the algorithm worked within, including a dose cap on the first prototype, and a safety committee approved every composition before manufacture and dosing, providing human-in-the-loop oversight of the trial.
The study used a generic drug selected for its established safety record and extensive published data. It was chosen to test the algorithm, not as a development candidate, and Quotient Sciences has no plans to progress it as a product.
"We set out to answer three questions," Lewis said. "Can the model learn the relationship between formulation composition and performance in humans, and if so, how quickly and how accurately? On the interim evidence, it can, and quickly enough that we expect to need less clinical testing to develop modified-release formulations for other molecules."
Dosing in the trial continues, and Quotient Sciences will report full data when the study is complete toward the end of this year. The work enhances Quotient Sciences' existing Translational Pharmaceutics® platform, which integrates drug product development, manufacturing and clinical testing. The AI-enhanced formulation development solution supports model-informed drug development by generating a digital twin that links formulation composition to in vitro performance and human pharmacokinetics.
For more information on Quotient Sciences' Translational Pharmaceutics® platform, please visit www.quotientsciences.com/translational-pharmaceutics/ai-formulation. Drug developers interested in applying AI-enhanced formulation development to an early-stage program are encouraged to contact the company's scientific team.
About Quotient Sciences
Quotient Sciences is an integrated CRDMO (contract research, development and manufacturing organization) providing services across the entire drug development and clinical pathway. Our flagship platform for drug development, Translational Pharmaceutics®, has been trusted by companies ranging from emerging biotechs to Fortune 50 pharmaceutical organizations for integrated drug product formulation, manufacturing and clinical testing. Enhanced with our new AI-driven formulation insights and backed by more than 20 years of experience, Translational Pharmaceutics® helps sponsors make better decisions earlier and advance towards proof-of-concept studies while reducing early development time, cost and risk. To learn more, visit quotientsciences.com.
View original content:https://www.prnewswire.com/news-releases/quotient-sciences-proprietary-ai-enhanced-solution-optimizes-formulation-in-clinical-study-302881862.html
SOURCE Quotient Sciences
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