Publications by authors named "Rahul Dhakne"

Background: Despite guideline recommendations, most patients with COPD do not undergo alpha-1 antitrypsin deficiency (AATD) testing and approximately 90% of people with AATD in the US remain undiagnosed. This study sought to develop a predictive model using real-world data to improve detection of AATD-positive patients in the general COPD population.

Methods: A predictive model using XGBoost was developed using the EVERSANA database, including longitudinal, patient-level medical claims, prescription claims, AATD-specific testing data, and electronic health records (EHR).

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Currently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism.

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Nowadays most of the CNS acting therapeutic molecules are failing in clinical trials due to efflux transporters at the blood brain barrier (BBB) which imparts resistance and poor ADMET properties of these molecules. CNS acting drug molecules interact with the BBB prior to their target site, so there is a need to develop predictive models for BBB permeability which can be used in the initial phases of drug discovery process. Most of the drug molecules are transported to the brain via passive diffusion which is explored extensively; on the other hand, the role of active efflux transporters in BBB permeability is unclear.

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