Role of physiologically based biopharmaceutics modeling in predicting and circumventing the drug-drug interactions of tyrosine kinase inhibitors with acid-reducing agents

Tyrosine kinase inhibitors (TKIs) are molecular targeting agents used to treat various types of cancer. During the treatment with TKIs, acid-reducing agents (ARAs) are prescribed to prevent gastric mucosal damage. However, this co-administration causes increased gastric pH resulting in reduced exposure to TKIs. Thus, avoidance of this interaction through formulation intervention is necessary to have better efficacy. The objective of the present work is to demonstrate the utility of physiologically based biopharmaceutics (PBBM) in predicting and circumventing the interactions of TKIs with ARAs. PBBM was developed for dasatinib, bosutinib, and gefitinib using physicochemical, pharmacokinetic, and physiological inputs. The models were validated against oral and intravenous clinical data. The model successfully predicted ARA interactions (stomach pH is changed to 5 to mimic ARA administration), that are in line with literature-reported data. Solubility generated in the presence of citric acid demonstrated enhanced solubility in the pH range of 4.5–6.8 for all drugs. Integration of enhanced solubility in PBBM demonstrated a nullified ARA effect for all drugs. This result indicated the possibility of dose reduction and reduced intestinal precipitation due to the acidifying effect of citric acid. Overall, PBBM successfully demonstrated potential in predicting and circumventing the ARA effect to enhance the efficacy of TKIs.

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Publication Details

Journal
Journal of Applied Pharmaceutical Science
Published
2025-01-01
DOI
https://doi.org/10.7324/japs.2025.234298
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Role of physiologically based biopharmaceutics modeling in predicting and circumventing the drug-drug interactions of tyrosine kinase inhibitors with acid-reducing agents

Sahadevan Rajesh Rashmi, Punna Rao Ravi, Praveen Sivadasu, Sivacharan Kollipara et al.
Journal of Applied Pharmaceutical Science
Computational Drug Discovery Methods
article

Role of physiologically based biopharmaceutics modeling in predicting and circumventing the drug-drug interactions of tyrosine kinase inhibitors with acid-reducing agents

Sahadevan Rajesh Rashmi, Punna Rao Ravi, Praveen Sivadasu, Sivacharan Kollipara, Chakravarthi Guntupalli
article en

Abstract

Tyrosine kinase inhibitors (TKIs) are molecular targeting agents used to treat various types of cancer. During the treatment with TKIs, acid-reducing agents (ARAs) are prescribed to prevent gastric mucosal damage. However, this co-administration causes increased gastric pH resulting in reduced exposure to TKIs. Thus, avoidance of this interaction through formulation intervention is necessary to have better efficacy. The objective of the present work is to demonstrate the utility of physiologically based biopharmaceutics (PBBM) in predicting and circumventing the interactions of TKIs with ARAs. PBBM was developed for dasatinib, bosutinib, and gefitinib using physicochemical, pharmacokinetic, and physiological inputs. The models were validated against oral and intravenous clinical data. The model successfully predicted ARA interactions (stomach pH is changed to 5 to mimic ARA administration), that are in line with literature-reported data. Solubility generated in the presence of citric acid demonstrated enhanced solubility in the pH range of 4.5–6.8 for all drugs. Integration of enhanced solubility in PBBM demonstrated a nullified ARA effect for all drugs. This result indicated the possibility of dose reduction and reduced intestinal precipitation due to the acidifying effect of citric acid. Overall, PBBM successfully demonstrated potential in predicting and circumventing the ARA effect to enhance the efficacy of TKIs.

Journal of Applied Pharmaceutical Science
Openalex Percentile: Top 92%
Computational Drug Discovery Methods
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