Psychotropic medication prescribing trends in a developmental-behavioural clinic during the COVID-19 pandemic.

AIM: Psychotropic medication prescribing among children with developmental-behavioural and mental health problems appears to be rising globally. We aim to examine the effects of the COVID-19 pandemic and rapid introduction of telehealth consultations on the prescribing trends and medication change in a large paediatric public hospital developmental-behavioural outpatient service. METHODS: Data for developmental-behavioural outpatient encounters from 23 March 2019 to 22 March 2021 were extracted from the electronic medical record; representing the 12 months following the conversion to telehealth consultations during the onset of COVID-19 pandemic and the 12 months prior to this change. Excel and Statistical Package for the Social Sciences were used to calculate percentages and logistic regression to compare psychotropic prescribing trends during both periods. RESULTS: During the pandemic, there were a total of 3201 encounters (92.0% telehealth), compared with 2759 encounters (1.6% telehealth) during the previous year. Despite the higher number of encounters during the pandemic, the rates of encounters with psychotropic medication prescriptions reduced compared to the previous 12 months (19.8% vs. 29.3%). Prescriptions made during COVID-19 were more likely to be provided at review visits, patients ≥12 years and during consultant led encounters. The reduction in prescriptions involved both new and follow-up psychotropic medications. The majority of follow-up medication dosages were left unchanged. CONCLUSIONS: Psychotropic prescribing rates were lower during the COVID-19 pandemic. Fewer new medications were commenced and most medication dosages were unchanged.

Disrupting 3D printing of medicines with machine learning.

3D printing (3DP) is a progressive technology capable of transforming pharmaceutical development. However, despite its promising advantages, its transition into clinical settings remains slow. To make the vital leap to mainstream clinical practice and improve patient care, 3DP must harness modern technologies. Machine learning (ML), an influential branch of artificial intelligence, may be a key partner for 3DP. Together, 3DP and ML can utilise intelligence based on human learning to accelerate drug product development, ensure stringent quality control (QC), and inspire innovative dosage-form design. With ML's capabilities, streamlined 3DP drug delivery could mark the next era of personalised medicine. This review details how ML can be applied to elevate the 3DP of pharmaceuticals and importantly, how it can expedite 3DP's integration into mainstream healthcare.