AMS Professorship Award for Professor Philip Shaw, King's College London

Academy funding would support a post-doc, augment computational resources and help me establish a deeply phenotyped clinical cohort that focuses on minoritized children with severe mental health challenges, often under-represented in research. Precision care. Academy funding for a post-doc and computational resources would support two projects, grounded in pilot work at NIH and poised for translation to meet pressing clinical needs. The first study explores a precision care approach whereby ADHD treatment choice is guided by the neural features that underpin each child’s symptoms. My group has already shown that response to psychostimulant medication, the mainstay of ADHD treatment, is tied to a specific set of neural features, a ‘ biotype’ that reflects function within cortico-striatal neural circuits. With AMS support, I could determine if other neural features, or 'biotypes' tied to ADHD, are distinguished by their response to other ADHD medications, such as atomoxetine, alpha-2 adrenergic agonists and behavioral treatment. This project could stratify children based on their ‘biotypes’ into the treatments most likely to help, an advance on the current time-consuming process of cycling through options until arriving at the optimal treatment. The second 'precision care' project focuses on prognosis. Recently, my group used machine learning to develop a tool that predicted the course of childhood ADHD into early adolescence at clinically meaningful levels. It achieved success by augmenting clinical and demographic data with brain-based measures, specifically the biotype measures of connectivity within cortico-striatal and limbic circuits. Predictive power was further boosted by adding a child’s polygenic score for ADHD, reflecting genetic liability to the disorder. With AMS support, I aim to refine and validate this pilot tool on multiple independent cohorts. These two projects exemplify how an AMS supported post-doc and computational resources would ‘add value’ to my research. I only recently gained access to seven cohorts that allow for refinement and external validation of my precision tools for prognosis and treatment choice. These neuroimaging and genomic data need to be processed from scratch on a pipeline my group developed at NIH and implemented at King’s to ensure exquisite quality control and data harmonization. This processing is computationally intensive and requires postdoctoral level skills in data analytics and programming. The Academy’s support would allow me to seize the rare opportunity of having both promising ‘pilot’ tools and access to the cohorts needed to take these tools to the clinic. A clinical cohort capturing diversity and complexity. Academy funding would also help me move towards more inclusive clinical research. It is acknowledged that most neuroimaging and genomic cohorts under-represent the very children we most need to understand: those from minoritized ethnic groups and those with the most severe symptoms. A major reason for my move to King’s was my aspiration to build a clinical cohort that captures such diversity and clinical complexity. Such cohorts are hard to fund initially, especially for an investigator new to the UK competing against more established groups. Academy funding would allow me to establish a cohort of 650 children with ADHD and related conditions, prioritizing those with most severe symptoms and ensuring we capture the diversity of our South London communities. This clinical cohort is complemented by a neurotypical cohort of 650 children that is already funded providing comparative ‘normative’ data for studies at PMC.