Challenges in Evaluating Drug Product Performance
From solid dosage forms to controlled and long-acting drugs, performance assessment is a critical stage in drug development. When anomalies and product performance differences arise, identifying the root cause can be time and resource consuming. In Quality by Design (QdB) approaches, this investigation is further important for optimizing processes and formulations.
For understanding performance results, the size, distribution, and uniformity of the drug components is an essential consideration. This includes the active pharmaceutical ingredient (API), porosity, and excipients (including lubricants, disintegrants, and pore formers). Conventional techniques lack the efficiency, resolution, and representativeness to characterize these microstructures. For example, evaluating API recrystallization in an amorphous solid dispersion requires high sensitivity and 3D visualization of the interconnected phases. Analyzing and correlating these microstructures with drug performance demands an innovative high-resolution technique.
As the designed release duration increases, development resources can increase exponentially, driving the need for a novel and more efficient characterization technique.
The DigiM Solution – Mechanistic Evaluation of Drug Release
DigiM provides unique image-based tools to quantify microstructure properties and understand performance behavior, providing direct support on product quality assessment on the final drug product, as opposed to the indirect characterization on intermediate or raw ingredients. Our image-based analytics visualizes and evaluates microstructure performance parameters with high sensitivity, high resolution, and 3D representativeness. With image-based release prediction, the performance of long-acting and controlled release products can be understood in a matter of weeks, rather than months and years of testing and reformulation.
DigiM provides a suite of novel tools to help assess performance of pharmaceutical products accurately, timely, and cost effectively. The mechanistic understandings obtained for these drug products has demonstrated to save millions of dollars of investment risked by suboptimal performance or lack of microstructure understanding.
DigiM’s imaged based release prediction provides a direct evaluation on the impact of microstructures on drug release.
Application Areas and Case Studies
For the development of long-acting implants, stents, and birth control devices, lengthy in vitro and in vivo testing cycles can take a heavy burden on formulation and process optimization. The DigiM family of image-based release prediction tools (patent pending) uses T0 samples to predict release performance in a matter of days, which saves tremendous time and resources by reducing the evaluation time from years (typical to in vitro and in vivo tests) to months. Coupled with the evaluation of microstructure property evaluation, these tools have been applied to accelerate the development of drug-eluting stents (DES), long-acting implants, intrauterine devices and systems (IUD/IUS), and vaginal rings.
With solid dosage forms, the final microstructure of the drug product can be a black box, with little known about the arrangement of internal ingredients. This makes the impact of drug release from tableting compaction, capsule filling, particle size, and excipients difficult to characterize. With high-resolution 3D imaging approaches and AI analytics, the impact of these factors can be studied thoroughly and non-destructively, preserving the sample for further testing and analysis. Our analysis workflow for solid dosage forms has been applied to tablets, capsules, minitablets, and intermediates such as spray dried particles and granules.
For locally acting drugs (e.g., microspheres, depot, lotion, cream, inhaler) performance is extremely difficult and costly to evaluate. DigiM uses non-invasive imaging, in-situ imaging, and AI-based image analytics to characterize the drug product, drug delivery platforms, and its imminent release environments. Costly end-point clinical study or error-prone in-vitro tests can be reduced or avoided.