Experimental drugs in clinical trials for COPD: artificial intelligence via machine learning approach to predict the successful advance from early-stage development to approval.

Journal: Expert opinion on investigational drugs

PMID: 37364225

Abstract

INTRODUCTION: Therapeutic advances in drug therapy of chronic obstructive pulmonary disease (COPD) really effective in suppressing the pathological processes underlying the disease deterioration are still needed. Artificial Intelligence (AI) via Machine Learning (ML) may represent an effective tool to predict clinical development of investigational agents.

Authors

Luigino Calzetta

Department of Medicine and Surgery, University of Parma, Parma, Italy.
Elena Pistocchini

Department of Experimental Medicine, University of Rome "Tor Vergata", Rome, Italy.
Alfredo Chetta

Department of Medicine and Surgery, University of Parma, Parma, Italy.
Paola Rogliani

Department of Experimental Medicine, University of Rome "Tor Vergata", Rome, Italy.
Mario Cazzola

Department of Experimental Medicine, University of Rome "Tor Vergata", Rome, Italy.

Keywords

Administration, Inhalation Adrenergic beta-2 Receptor Agonists Artificial Intelligence Bayes Theorem Bronchodilator Agents Humans Machine Learning Muscarinic Antagonists Pulmonary Disease, Chronic Obstructive

External Resources

View on PubMed Access via DOI PubMed (37364225)

Experimental drugs in clinical trials for COPD: artificial intelligence via machine learning approach to predict the successful advance from early-stage development to approval.

Abstract

Authors

Keywords

External Resources

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