Effect of Compaction Pressure on the Enzymatic Activity of Pancreatin in Directly Compressible Formulations

Tableting of biomolecules is a challenging formulation phase due to their sensitivity to various process parameters, such as compression pressure, process dynamics, or the temperature generated. In the present study, pancreatin was employed as a model enzyme mixture, which was formulated in tablet form utilizing the synergistic effects of brittle and plastic excipients (dibasic calcium phosphate and microcrystalline cellulose, respectively). The effect of varying compaction pressure and lubricant concentration on the generated temperature and enzymatic activity was evaluated. The tablets were analyzed for pancreatin content and the activity of two enzymes (protease and amylase) using pharmacopoeial tests. This study indicated that the formulations proposed here allow tableting over a wide range of compaction pressures without adversely affecting pancreatin content and its enzymatic activity

A Rational Approach to Predicting Immediate Release Formulation Behavior in Multiple Gastric Motility Patterns: A Combination of a Biorelevant Apparatus, Design of Experiments, and Machine Learning

Gastric mechanical stress often impacts drug dissolution from solid oral dosage forms, but in vitro experiments cannot recreate the substantial variability of gastric motility in a reasonable time. This study, for the first time, combines a novel dissolution apparatus with the design of experiments (DoE) and machine learning (ML) to overcome this obstacle. The workflow involves the testing of soft gelatin capsules in a set of fasted-state biorelevant dissolution experiments created with DoE. The dissolution results are used by an ML algorithm to build the classification model of the capsule’s opening in response to intragastric stress (IS) within the physiological space of timing and magnitude. Next, a random forest algorithm is used to model the further drug dissolution. The predictive power of the two ML models is verified with independent dissolution tests, and they outperform a polynomial-based DoE model. Moreover, the developed tool reasonably simulates over 50 dissolution profiles under varying IS conditions. Hence, we prove that our method can be utilized for the simulation of dissolution profiles related to the multiplicity of individual gastric motility patterns. In perspective, the developed workflow can improve virtual bioequivalence trials and the patient-centric development of immediate-release oral dosage forms