Drug metabolism in the lungs: opportunities for optimising inhaled medicines. (4th May 2021)

• Record Type: Journal Article
• Authors: Enlo-Scott, Zachary; Bäckström, Erica; Mudway, Ian; Forbes, Ben
• Is Part Of: Expert opinion on drug metabolism and toxicology. Volume 17:Number 5(2021)
• Page Start: 611
• Page End: 625
• Publication Date: 2021-05-04
• Subjects: Respiratory -- pulmonary -- drug metabolism -- lung metabolism -- inhaled drugs -- pharmacokinetics -- inhalation toxicology -- pro-drug -- soft drug; Drugs -- Toxicology -- Periodicals; Drugs -- Metabolism -- Periodicals; 615.7
• DOI: 10.1080/17425255.2021.1908262
• Languages: English
• ISSNs: 1742-5255

Abstract

ABSTRACT: Introduction: The lungs possess many xenobiotic metabolizing enzymes which influence the pharmacokinetics and safety of inhaled medicines. Anticipating metabolism in the lungs provides an opportunity to optimize new inhaled medicines and overcome challenges in their development. Areas covered: This article summarizes current knowledge on xenobiotic metabolizing enzymes in the lungs. The impact of metabolism on inhaled medicines is considered with examples of how this impacts small molecules, biologics and macromolecular formulation excipients. Methods for measuring and predicting xenobiotic lung metabolism are critically reviewed and the potential for metabolism to influence inhalation toxicology is acknowledged. Expert opinion: Drugs can be optimized by molecular modification to (i) reduce systemic exposure using a 'soft drug' approach, (ii) improve bioavailability by resisting metabolism, or (iii) use a prodrug approach to overcome pharmacokinetic limitations. Drugs that are very labile in the lungs may require a protective formulation. Some drug carriers being investigated for PK-modification rely on lung enzymes to trigger drug release or biodegrade. Lung enzyme activity varies with age, race, smoking status, diet, drug exposure and preexisting lung disease. New experimental technologies to study lung metabolism include tissue engineered models, improved analytical capability and in silico models.