Professor Daniel Markl
Strathclyde Institute of Pharmacy and Biomedical Sciences
Prize And Awards
- Recipient
- 2020
- Recipient
- 2020
- Recipient
- 2019
- Recipient
- 2016
- Recipient
- 2010
Publications
- , Reynolds Gavin, Yates Catherine, , Upadhyay Pratik P, ,
- International Journal of Pharmaceutics Vol 697 (2026)
- , Abrahms茅n-Alami Susanna, Clark Catriona, D枚rr Frederik, , Ketolainen Jarkko, Lindow Morten, Mantanus J茅r么me, Rantanen Jukka, Reynolds Gavin, Robertson Amy,
- European Journal of Pharmaceutical Sciences Vol 220 (2026)
- , , , Rantanen Jukka,
- Journal of Pharmaceutical Sciences (2026)
- , , Hou Peter, , , , , Portela Victor, Boulay Quentin, Thiolliere Roland, Stark Ashley, Schwartz Jean-Jacques, Guerin Jerome, Maloney Andrew GP, Moldovan Alexandru A, Reynolds Gavin, Mantanus J茅r么me, Clark Catriona, Chapman Paul, ,
- Nature Communications Vol 17 (2026)
- , , ,
- CMAC Open Days 2026 (2026)
- Gorecki Jon, Murphy Keir N, , Burnett Andrew D, Naftaly Mira
- 2025 50th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) (2026)
Research Interests
Our laboratory conducts multidisciplinary research at the intersection of materials, processes, products, and performance, with the goal of transforming how medicines are designed, developed, and manufactured. We seek to establish a fundamental, predictive understanding of how material properties and processing conditions jointly determine product structure, quality, and performance.
Central to our approach is the coupling of self-driving laboratories, advanced measurement techniques, and digital process and product design. By integrating automation, high-throughput experimentation, real-time analytics, and data-driven modeling, we aim to dramatically accelerate development timelines while improving robustness, efficiency, and knowledge generation across the pharmaceutical lifecycle.
Our research includes the development of predictive systems, in-silico design methods, and autonomous experimental platforms for drug product development and manufacturing. These tools enable rapid exploration of complex formulation and process spaces, support rational decision-making, and reduce reliance on trial-and-error experimentation. Ultimately, our work lays the foundation for adaptive, intelligent manufacturing systems that deliver higher-quality medicines more efficiently and reliably.
Professional Activities
- Speaker
- 2025
- Speaker
- 2025
- Speaker
- 2025
- Speaker
- 2024
- Speaker
- 2024
- Speaker
- 2024
Projects
- Markl, Daniel (Principal Investigator) Florence, Alastair (Co-investigator)
- 01-Jan-2025 - 30-Jan-2026
- Markl, Daniel (Principal Investigator) Florence, Alastair (Co-investigator) Johnston, Blair (Co-investigator)
- 01-Jan-2025 - 31-Jan-2026
- Nordon, Alison (Principal Investigator) Littlejohn, David (Co-investigator) Markl, Daniel (Co-investigator)
- 01-Jan-2025 - 30-Jan-2025
- Fitzpatrick, Stephen (Principal Investigator) Florence, Alastair (Principal Investigator) Florence, Alastair (Co-investigator) Johnston, Blair (Co-investigator) Markl, Daniel (Co-investigator)
- 01-Jan-2025 - 30-Jan-2025
- Markl, Daniel (Principal Investigator) Macdonald, Janine (Co-investigator)
- 25-Jan-2024 - 19-Jan-2024
- Markl, Daniel (Principal Investigator) Li, Jun (Co-investigator) Jahangir, Reehab (Research Co-investigator)
- 01-Jan-2024 - 01-Jan-2028
Contact
Professor
Daniel
Markl
Strathclyde Institute of Pharmacy and Biomedical Sciences
Email: daniel.markl@strath.ac.uk
Tel: 444 7115