Internacjonalizacja praw człowieka. Kilka refleksji / Adam Jamróz

Zdigitalizowano i udostępniono w ramach projektu pn. Rozbudowa otwartych zasobów naukowych Repozytorium Uniwersytetu w Białymstoku, dofinansowanego z programu „Społeczna odpowiedzialność nauki” Ministra Edukacji i Nauki na podstawie umowy SONB/SP/512497/202114515

Prawa i wolności jednostki na gruncie francuskich konstytucji

Zdigitalizowano i udostępniono w ramach projektu pn. Rozbudowa otwartych zasobów naukowych Repozytorium Uniwersytetu w Białymstoku, dofinansowanego z programu „Społeczna odpowiedzialność nauki” Ministra Edukacji i Nauki na podstawie umowy SONB/SP/512497/2021Uniwersytet w Białymstoku20722

O wywłaszczeniu nieruchomości na gruncie Konstytucji RP. Kilka uwag

Zdigitalizowano i udostępniono w ramach projektu pn. Rozbudowa otwartych zasobów naukowych Repozytorium Uniwersytetu w Białymstoku, dofinansowanego z programu „Społeczna odpowiedzialność nauki” Ministra Edukacji i Nauki na podstawie umowy SONB/SP/512497/202146648

Data-driven modeling of the bicalutamide dissolution from powder systems

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