Dr Cosmika Goswami
Research Associate
Strathclyde Institute of Pharmacy and Biomedical Sciences
Personal statement
Biostatistical Researcher | Computational Biologist
I am a bioinformatician with over twelve years of experience in developing computational tools for analysing clinical healthcare data and bacterial population genetics using whole genome sequencing. My expertise lies in mathematical and statistical modelling, particularly Markov Chains, and applying machine learning techniques in bioinformatics and epidemiology.
I hold a Ph.D. in Mathematical Statistics from the Indian Institute of Technology Guwahati, where I specialised in Markov Chain modelling. My postdoctoral research took me to the University of Edinburgh and the University of Glasgow before I joined the University of Strathclyde as a Research Associate.
Area of Expertise
As a Researcher at the University of Strathclyde, I specialise in bioinformatics with a particular focus on the application of machine learning methods and AI tools to analyse complex clinical and biological datasets. My work leverages advanced computational techniques to uncover insights in areas such as antipsychotics and antibiotics, aiming to improve therapeutic strategies and drug efficacy, to understand complex biological phenomena and to develop of more effective healthcare solutions.
Machine Learning in Bioinformatics:
I am proficient in applying supervised and unsupervised machine learning algorithms to bioinformatics data, enabling the identification of patterns and predictive models for clinical and biological outcomes. By using decision trees, random forests, and support vector machines (SVMs), hidden relationships can be uncovered within datasets, contributing to the optimisation of treatment regimens in antipsychotics and antibiotic research.
AI Tools for Data Analysis:
Integrating AI tools such as neural networks, deep learning, and natural language processing (NLP) large-scale datasets, ranging from clinical records to drug response data, can be processed. These tools allow to build more accurate predictive models for personalised medicine in clinical drugs like antipsychotics, as well as to enhance antimicrobial resistance studies by predicting resistance patterns and drug interactions.
Core Skills and Tools:
- Expertise in machine learning algorithms and techniques tailored to bioinformatics
- Advanced skills in AI-driven data analysis for high-dimensional biological datasets
- Experience with data pre-processing, feature engineering, and model validation for machine learning applications
- Proficient in statistical analysis and data visualisation to communicate findings clearly and effectively
Publications
- Evaluate and compare different decision support tools used for the management of high-dose antipsychotic prescriptions : a scoping review
- Rae Mia, Goswami Cosmika, Ferguson Eve, Bennie Marion
- European Drug Utilisation Conference (EuroDURG) (2025)
- Comparing and analysing tools for calculating anticholinergic burden in psychiatric medication
- Fraser Hannah, Goswami Cosmika, Ferguson Eve, Bennie Marion
- European Drug Utilisation Conference (EuroDURG) (2025)
- Compare the definitions used to calculate high-dose antipsychotics : a scoping review
- Bell Eve, Goswami Cosmika, Ferguson Eve, Bennie Marion
- European Drug Utilisation Conference (EuroDURG) (2025)
- Clinical decision support (CDS) tools for medicine optimisation in hospitals
- Ferguson Eve, Goswami Cosmika, Bennie Marion, Kurdi Amanj
- The NORDIC Social Pharmacy Conference 2025 (2025)
- Medicines in acute and chronic care in Scotland (MACCS) : a new research data resource
- Goswami Cosmika, Mueller Tanja, Ferguson Eve, Pearson Ewan, Bedair Khaled, Bennie Marion, Kurdi Amanj
- European Drug Utilization Research Group conference 2025 (EuroDURG) (2025)
- UK Antimicrobial Virtual Registry-Scotland : innovative methods for monitoring the use and effectiveness of newly licensed antimicrobial
- Turgal Ebru, Goswami Cosmika, Mueller Tanja, Bennie Marion, Sneddon Jacqueline, Seaton Ronald Andrew, Sandoe Jonathan, Parr Rebecca, Macfarlane Gary, Jones Gareth, Kurdi Amanj
- European Drug Utilization Research Group conference 2025 (EuroDURG) (2025)
Research Interests
My research focuses on:
- Investigating the impact of mental health prescriptions in acute hospital care settings.
- Modelling and managing big healthcare data from NHS and Health Protection Scotland.
- Applying machine learning and network analysis for epidemiological studies.
- Analysing genomic data from pathogenic bacteria using sequencing technologies (MinION, PacBio, Illumina).
- Developing automated Python-based pipelines for large-scale genomic and healthcare data analysis.
Current Projects
Impact of High-Dose Antipsychotic Prescribing in Acute Care Settings
- Investigating the prevalence, clinical characteristics, and associated risks of high-dose antipsychotic prescribing in hospital settings across Scotland.
- Assessing the short-term and long-term clinical outcomes of high-dose versus standard-dose antipsychotic regimens using statistical and machine learning approaches.
- Supporting antipsychotic stewardship efforts by identifying factors influencing high-dose prescribing and improving evidence-based decision-making in acute care settings.
UKAR Virtual Registry (Scotland)
- Utilising record linkage of administrative health datasets to assess the real-world use, effectiveness, and safety of recently licensed antimicrobial agents (RLAs) in Scottish hospitals.
- Investigating patient characteristics, treatment regimens, microbiological investigations, and clinical outcomes associated with RLAs.
- Supporting antimicrobial stewardship efforts by identifying gaps in current prescribing practices and contributing to more judicious use of antimicrobials.
Previous Projects
Scottish Healthcare Associated Infection Prevention Institute (SHAIPI)
- Large-scale genomic epidemiology study on pathogenic bacteria.
- Development of computational pipelines for whole genome sequencing analysis.
- Collaborative research involving multiple Scottish universities and NHS Scotland.
Molecular Epidemiology of Clostridium difficile in Scotland
- Developed novel research methods combining genomic analysis with health informatics.
- Analysed bacterial population structures and antimicrobial resistance patterns.
- Project funded by SIRN (Scottish Infection Research Network).
Genomic Selection in Sitka Spruce Trees
- Investigated genetic markers for tree breeding strategies.
- Applied statistical modelling for predicting genomic evaluation accuracy.
- Project funded by the European Commission FP7.
Professional Activities
- NORDIC Social Pharmacy Conference 2025
- Organiser
- 4/6/2025
- Bioinformatics Workflows with Snakemake
- Participant
- 2021
- Introduction to Omics
- Participant
- 2021
- Bioinformatics in analysis of WHO top listed bacterial genomes
- Speaker
- 2019
- Changing Epidemiology of E.coli and S. aureus in Scotland
- Speaker
- 2018
- Identification of Transmission Events by Linking Clinical Data with Whole Genome Sequences of S.aureus bacteraemia across Scottish Health Boards
- Speaker
- 2018
Projects
- HDR-UK Health Driver Programme for QQ2: Medicines in Acute and Chronic Care
- Bennie, Marion (Principal Investigator) Kurdi, Amanj (Co-investigator) Goswami, Cosmika (Researcher)
- 01-Jan-2023 - 31-Jan-2028
- Development a virtual Antimicrobial Registry
- Kurdi, Amanj (Principal Investigator) Bennie, Marion (Co-investigator) Goswami, Cosmika (Researcher) Turgal, Ebru (Researcher)
- 01-Jan-2022 - 30-Jan-2025
- Whole-genome sequencing of potable water derived Cupriavidus species
- Leanord, Alistair (Principal Investigator) Evans, Thomas Ronald Jeffry (Principal Investigator) Holden, Matthew T. G. (Principal Investigator) Goswami, Cosmika (Co-investigator) Fox, Stephen (Co-investigator)
- CoE research Grant of £28,594 for research of ‘Whole-genome sequencing of potable water derived Cupriavidus species’ in collaboration with NHS Scotland. The whole-genome sequencing was used to detect Stenotrophomonas maltophilia infection and to identify the type of circulating strain within the hospital environment to study its plausible transmissibility to humans. This gives a better understanding of the local spread of the infection, while compared to global data, and also for infection prevention within hospitals or healthcare institutes.
- 01-Jan-2021 - 31-Jan-2022
- Carbapenemase-producing Enterobacteriaceae (CPE)s - AMR Seed Funding Project by SULSA
- Goswami, Cosmika (Principal Investigator) Fox, Stephen (Principal Investigator)
- 04-Jan-2018 - 30-Jan-2019
- Scottish Healthcare Associated Infection Prevention Institute (SHAIPI)
- Leanord, Alistair (Principal Investigator) Evans, Thomas R. (Principal Investigator) Goswami, Cosmika (Researcher) Fox, Stephen (Researcher) Holden, Matthew T. G. (Principal Investigator)
- 24-Jan-2015 - 10-Jan-2023
- Molecular Epidemiology of Clostridium difficile in Scotland: Developing novel, clinically applicable research methods to Combine Genomic Analysis with Health Informatics
- Douce, Gillian (Principal Investigator) Marwick, Charis (Principal Investigator) Goswami, Cosmika (Researcher) Ijaz, Umer Zeeshan (Research Co-investigator)
- 05-Jan-2014 - 30-Jan-2015
Contact
Dr
Cosmika
Goswami
Research Associate
Strathclyde Institute of Pharmacy and Biomedical Sciences
Email: cosmika.goswami@strath.ac.uk
Tel: 01415482478