B3799 - Exploratory ML Based Longitudinal Modelling Approaches to Map Genetic-Phenotypic Multi-Trait Predictors of Fibrosis - 28/06/2021

B number: 
Principal applicant name: 
Nathan Lawless | Boehringer Ingelheim (Germany)
Zhihao Ding, Dr
Title of project: 
Exploratory ML Based Longitudinal Modelling Approaches to Map Genetic-Phenotypic Multi-Trait Predictors of Fibrosis
Proposal summary: 

Global Computational Biology & Digital Sciences (GCBDS) is a department in Boehringer Ingelheim’s Innovation Unit (IU) and is principally engaged in early discovery research programs. In 2020 the IU embarked on a curriculum to more deeply explore healthcare databases and biobank initiatives. The overall objective of the program is to explore advanced analytical methods to harness genomic & phenotypic data in order to better understand causative pathological mechanisms for disease which have the long-term potential to support patients.

Boehringer has a longstanding heritage in a number of unmet areas of medical need we consider our core disease areas; These include cardio-metabolic diseases, central nervous system diseases, immunology, respiratory and oncology as well as fields of active research that are currently covered by Research Beyond Borders (e.g. infectious diseases or regenerative medicines).

As part of BI’s preparatory research, a meta-analysis was undertaken to identify initiatives which focus on longitudinal multi-generational familial analysis in the field of fibrosis research (lung, liver). Two area’s of interest are of high priority (i) developing computational based method development programs focused on accurate and interpretable statistical approaches and (ii) Exploring methods to undertake trans biobank analysis on individuals from diverse ethnic backgrounds, but sharing similar phenotypic traits.

Impact of research: 
As previously outlined, Boehringer has a longstanding heritage in treating patients with a range of heterozygous respiratory diseases often underpinned by fibrosis. In these early exploratory analysis we aim to shed new light on the disease progression underpinning fibrosis and leverage our existing experience to support disease understanding.
Date proposal received: 
Saturday, 19 June, 2021
Date proposal approved: 
Monday, 21 June, 2021
Bioinformatics, Addiction - e.g. alcohol, illicit drugs, smoking, gambling, etc., Allergy, Epilepsy, Gastrointestinal, Hypertension, Incontinence, Infection, Learning difficulty, Mental health, Obesity, Pain, Pregnancy - e.g. reproductive health, postnatal depression, birth outcomes, etc., Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Respiratory - asthma, Sexually transmitted diseases, chlamydia, gonorrhoea, Developmental disorders - autism, Cancer, Chronic fatigue, Cognitive impairment, Congenital abnormalities, Diabetes, Eating disorders - anorexia, bulimia, Computer simulations/modelling/algorithms, Gene mapping, RNA, Statistical methods, GWAS, Mass spectrometry, Medical imaging, Metabolomics, Microarrays, NMR, Proteomics, Qualitative study, Ageing, Biomarkers - e.g. cotinine, fatty acids, haemoglobin, etc., Equipment - MRI, Endocrine - endocrine disrupters, ENT - hearing, Environment - enviromental exposure, pollution, Epigenetics, Expression, Genetic epidemiology, Genetics, Genomics, Genome wide association study, Blood pressure, Immunity, Linkage, Liver function, Mendelian randomisation, Statistical methods, Whole genome sequencing, BMI, Cardiovascular, Cohort studies - attrition, bias, participant engagement, ethics, Childhood - childcare, childhood adversity, Cognition - cognitive function, Communication (including non-verbal), Development