Machine Learning ADME Models in Practice: Four Guidelines from a Successful Lead Optimization Case Study.

Optimization of the ADME properties and pharmacokinetic (PK) profile of compounds is one of the critical activities in any medicinal chemistry campaign to discover a future clinical candidate. Finding ways to expedite the process to address ADME/PK shortcomings and reduce the number of compounds to synthesize is highly valuable. This article provides practical guidelines and a case study on the use of ML ADME models to guide compound design in small molecule lead optimization.

Can machine learning improve patient selection for cardiac resynchronization therapy?

Rationale: Multiple clinical trials support the effectiveness of cardiac resynchronization therapy (CRT); however, optimal patient selection remains challenging due to substantial treatment heterogeneity among patients who meet the clinical practice guidelines.

Objective: To apply machine learning to create an algorithm that predicts CRT outcome using electronic health record (EHR) data avaible before the procedure.

Methods And Results: We applied machine learning and natural language processing to the EHR of 990 patients who received CRT at two academic hospitals between 2004-2015.

'Autistic' local processing bias also found in children gifted in realistic drawing.

We investigated whether typically-developing children with a gift for drawing realistically show the local processing bias seen in individuals with autism spectrum disorder (ASD). Twenty-seven 6-12 year-olds made an observational drawing (scored for level of realism) and completed three local processing tasks, and parents completed the Childhood Asperger Syndrome Test (CAST). Drawing score predicted local processing performance on all tasks independently of verbal IQ, age, and years of art lessons.

Temporal lobe sulco-gyral pattern anomalies in schizophrenia: an in vivo MR three-dimensional surface rendering study.

Neuroanatomical and histological findings from post-mortem brains, as well as in vivo findings from magnetic resonance imaging (MRI) studies, suggest the presence of morphologic temporal lobe abnormalities in schizophrenia. To determine whether or not sulco-gyral pattern abnormalities in the temporal lobe could be detected in vivo, we applied computerized surface rendering techniques to MR data sets in order to make both qualitative and quantitative analyses of three-dimensional reconstructions of the temporal and frontal cortex in 15 schizophrenic patients and 15 normal controls. The qualitative analysis, based on a visual classification of the temporal lobe sulco-gyral pattern by 4 raters blind to diagnosis, showed that in schizophrenics there was a more vertical orientation to the sulci in the left temporal lobe, with an interrupted course of sulci due to gyri coursing across the sulci.

Neuropsychological correlates of MRI temporal lobe abnormalities in schizophrenia.

Objective: The authors evaluated the neuropsychological correlates of temporal lobe abnormalities in schizophrenic patients.

Method: Fifteen schizophrenic patients underwent assessment of memory, by the Wechsler Memory Scale--Revised, and abstraction/categorization, by the similarities subtest of the Wechsler Adult Intelligence Scale--Revised and the Wisconsin Card Sorting Test. Neuropsychological tests of motor and constructional functions were used as control tasks.