Data-Driven Modeling of the Bicalutamide Dissolution from Powder Systems

Abstract

Low solubility of active pharmaceutical compounds (APIs) remains an important challenge in dosage form development process. In the manuscript, empirical models were developed and analyzed in order to predict dissolution of bicalutamide (BCL) from solid dispersion with various carriers. BCL was chosen as an example of a poor watersoluble API. Two separate datasets were created: one from literature data and another based on in-house experimental data. Computational experiments were conducted using artificial intelligence tools based on machine learning (AI/ML) with a plethora of techniques including artificial neural networks, decision trees, rule-based systems, and evolutionary computations. The latter resulting in classical mathematical equations provided models characterized by the lowest prediction error. In-house data turned out to be more homogeneous, as well as formulations were more extensively characterized than literature-based data. Thus, in-house data resulted in better models than literature-based data set. Among the other covariates, the best model uses for prediction of BCL dissolution profile the transmittance from IR spectrum at 1260 cm −1 wavenumber. Ab initio modeling-based in silico simulations were conducted to reveal potential BCL-excipients interaction. All crucial variables were selected automatically by AI/ML tools and resulted in reasonably simple and yet predictive models suitable for application in Quality by Design (QbD) approaches. Presented data-driven model development using AI/ML could be useful in various problems in the field of pharmaceutical technology, resulting in both predictive and investigational tools revealing new knowledge.

Physicochemical Profile of Antiandrogen Drug Bicalutamide: Solubility, Distribution, Permeability

“…The BCL aqueous solubility measured in this work ( Table 1 ) was in agreement with the values reported in our previous study [ 12 ] and the results of Mendyk et al [ 10 ]. However, it is approximately 2-fold lower than was estimated by Patil et al [ 11 ].…”

“…In accordance with the extremely poor aqueous solubility recognized at approximately 3.7 μg·mL −1 [ 10 ] and 8.85 mg·L −1 [ 11 ] and good intestinal absorption, BCL is classified as a BCS (Biopharmaceutics Classification System) class II drug. Two BCL polymorphic modifications that differ from each other in stability and solubility in water have been proved [ 12 ].…”

Another Move towards Bicalutamide Dissolution and Permeability Improvement with Acetylated β-Cyclodextrin Solid Dispersion

“…The poor solubility of BCL in an aqueous solution was estimated elsewhere [ 4 , 5 , 8 ] earlier. Moreover, several attempts to improve the solubility have been undertaken (see the Introduction section).…”

Microfluidic Synthesis of Indomethacin-Loaded PLGA Microparticles Optimized by Machine Learning

“…Machine learning is an AI technique whereby computers can adjust their actions (e.g., making predictions). In addition, artificial neural networks (ANNs) are commonly used machine learning techniques used in pharmaceutics because of their powerful ability to model nonlinear relationships ( Damiati et al, 2017 ; Mendyk et al, 2020 ). A typical ANN structure consists of input, hidden, and output layers.…”