Measuring pain in infants

Pain experienced in early life has negative long-term consequences for an infant's neurological development, but measuring pain is notoriously difficult in this non-verbal infant population. Quantifying pain experience in infants using non-verbal surrogate pain measures is an essential prerequisite for preventing and treating pain, and the European Medicines Agency has identified this as a priority area for development. Pain, together with other external stressors, can contribute to physiological instability more generally.
The initial aims of this DPhil project are to develop an analytical approach to measuring physiological instability in the context of external stressors. Initially this will use an existing dataset; 30 newborn babies (that were collected as part of the Poppi trial, Lancet 2018) had electroencephalographic (EEG) and physiological data (including heart rate, respiratory rate and oxygen saturation) collected during and after a (presumably painful) routine eye exam to diagnose retinopathy of prematurity. By investigating changes in EEG activity and the physiological characteristics that are evoked by the clinical procedure, features that are associated with pain experience and physiological instability can be identified. Once important characteristics of physiological instability have been identified, a composite measure can be formed and generalised using additional datasets.
The DPhil project could be further developed such that these measures could be validated so they are suitable for use an outcome measures in clinical trials that aim to investigate the efficacy of pharmacological and non-pharmacological analgesics in infants. This could also reduce the cost of conducting clinical trials in infants. A potential direction for the project would be to partner with industry and regulatory agencies to create an evidence base that could lead towards the licencing of analgesics in infants.
Quantifying pain experience in infants is an open problem in clinical practice, and all the analyses described are novel in the context of the neonatal population.
The project includes industrial collaboration with Reckitt Benckiser (RB). In addition, parts of the project outcomes may be included in the development of a new medical device. The proposal for this device has been accepted for assessment by Oxford University Innovation.
This project falls within the EPSRC "Clinical technologies (excluding imaging)" research area. In particular it contributes to the Ambitions, within the EPSRC's Healthy Nation Outcome, to "transform community health and care" and "optimise diagnosis and treatment". Parts of the project can also be expected to fall within the EPSRC "Medical imaging (including medical image and vision computing)" and "Analytical science" research areas.

The UK's world-leading position in biomedical research is critically dependent upon training scientists with the cutting-edge research skills and technological know-how needed to drive future scientific advances. Since 2009, the EPSRC and MRC CDT in Systems Approaches to Biomedical Science (SABS) has been working with its consortium of 22 industrial and institutional partners to meet this training need.

Over this period, our partners have identified a growing training need caused by the increasing reliance on computational approaches and research software. The new EPSRC CDT in Sustainable Approaches to Biomedical Science: Responsible and Reproducible Research - SABS:R^3 will address this need. By embedding a sustainable approach to software and computational model development into all aspects of the existing SABS training programme, we aim to foster a culture change in how the computational tools and research software that now underpin much of biomedical research are developed, and hence how quantitative and predictive translational biomedical research is undertaken.

As with all CDT Programmes, the future impact of SABS:R^3 will be through its alumni, and by the culture change that its training engenders. By these measures, our existing SABS CDT is already proving remarkably successful. Our alumni have gone on to a wide range of successful careers, 21 in academic research, 19 in industry (including 5 in SABS partner companies) and the other 10 working in organisations from the Office of National Statistics to the EPSRC. SABS' unique Open Innovation framework has facilitated new company connections and a high level of operational freedom, facilitating 14 multi-company, pre-competitive, collaborative doctoral research projects between 11 companies, each focused on a SABS student.

The impact of sustainable and open computational approaches on biomedical research is clear from existing SABS' student projects. Examples include SAbDab which resulted from the first-ever co-sponsored doctorate in SABS, by UCB and Roche. It was released as open source software, is embedded in the pipelines of several pharmaceutical companies (including UCB, Medimmune, GSK, and Lonza) and has resulted in 13 papers. The SABS student who developed SAbDab was initially seconded to MedImmune, sponsored by EPSRC IAA funding; he went on to work at Roche, and is now at BenevolentAI. Similarly, PanDDA, multi-dataset X-ray crystallographic software to detect ligand-bound states in protein complexes is in CCP4 and is an integral part of Diamond Light Source's XChem Pipeline. The SABS student who developed PanDDA was awarded an EMBO Fellowship.

Future SABS:R^3 students will undertake research supported by both our industrial partners and academic supervisors. These supervisors have a strong track record of high impact research through the release of open source software, computational tools, and databases, and through commercialisation and licensing of their research. All of this research has been undertaken in collaboration with industrial partners, with many examples of these tools now in routine use within partner companies.

The newly focused SABS:R^3 will permit new industrial collaborations. Six new partners have joined the consortium to support this new bid, ranging from major multinationals (e.g. Unilever) to SMEs (e.g. Lhasa). SABS:R^3 will continue to make all of its research and teaching resources publicly available and will continue to help to create other centres with similar aims. To promote a wider cultural change, the SABS:R^3 will also engage with the academic publishing industry (Elsevier, OUP, and Taylor & Francis). We will explore novel ways of disseminating the outputs of computational biomedical research, to engender trust in the released tools and software, facilitate more uptake and re-use.