Aparito welcomes Data Scientist Sandra Komarzynski to the team. Sandra joined in April 2020 and brings over five years’ experience in a wide range of clinical research areas.
I am a biomedical engineer with 5+ years experience in cancer clinical research. I am interested in using mHealth technologies to remotely monitor biological rhythms and symptoms in patients outside the hospital setting. I have developed expertise in large database management, biological time-series collection and analysis from wearables. I have been involved in clinical trials support, design, conduct, monitoring and staff training.
In my current role as Data Scientist at Aparito, I build analytical tools for health data using wearable devices and the Atom5™ platform for rare disease and cancer patients. My tasks involve data collection monitoring, data cleaning and analysis using tailored algorithms. In my most recent project, I focused on the feasibility assessment of remote surveillance of oncological patients during the Covid-19 outbreak – this involved the collection of Covid-related symptoms and physiological data recorded by a wrist-worn wearable device and the Atom5™ Platform. For this project, I was responsible for the assessment of patients’ engagement and adherence, analysis of the time series and the descriptive statistics.
Working at the French National Institute for Health and Medical Research (INSERM), I took part in a National project involving ten industrial, academic and clinical partners, that developed the first mobile platform for the remote multi-dimensional monitoring of chronic diseases [1]. I was responsible for linking the technical developments of the platform with the targeted users, including patients and health professionals; this included, managing the logistics, training, recruiting participants, monitoring the data collection and performing data analysis throughout the pilot tests in cancer patients. In my research role at Warwick Medical School within the Cancer Chronotherapy Team, I was involved in a study aimed at capturing the intra- and inter-variabilities in circadian rhythms of healthy volunteers [2]. The study recruited 30 participants who monitored their circadian rhythms for 1 to 3 weeks using telecommunicating devices such as a chest sensor, a wrist actigraph, and a bodyweight scale.
My further research in healthy volunteers was aimed at predicting the core body temperature from non-invasive physiological measures and questionnaires. I participated in the design of the study and was responsible for the technical support, data monitoring, management and analysis. Forty subjects were recruited and monitored, their core body temperature was measured using an eHealth ingestible pill, physical activity and skin temperature were recorded by a chest sensor during the subject’s daily life for a duration of one week. The subjects self-collected saliva samples for hormone level determination. The prediction model developed, was able to predict core body temperature phase from sex, score from a chronotype questionnaire, and two tele-monitored circadian parameters [3].
I was also involved in a French study that aimed to identify circadian and sleep disruption due to shift work in 200 nurses [paper in preparation]. The nurses provided a general questionnaire including demographics, work and medical history, sleep habits and medication use. They completed a chronotype questionnaire, wore a telemonitoring chest sensor and completed a precise work and sleep diary for a week. I coordinated the circadian rhythms analyses.
In order to find actionable determinants of circadian and sleep disruption in cancer patients, I helped design a multi-centre (5 in UK) observational clinical study. We investigated potential determinants of disruption in a number of tele-monitored circadian parameters, hormones and questionnaires. Patients took part in the study for 1 week of remote monitoring [paper submitted]. I was involved in the study set-up, clinical staff training, and study monitoring as well as the data validation, management and analysis. I developed analytics tools and was responsible for the time series analysis. Outside of work, I enjoy travel and photography.
References:
- Maurice M et al., Innovative Project for Domomedicine Deployment: The PiCADo Pilot Project. eTELEMED 2015.
- Komarzynski S et al., Relevance of a Mobile Internet Platform for Capturing Inter- and Intrasubject Variabilities in Circadian Coordination During Daily Routine: Pilot Study. J Med Internet Res 2018
- Komarzynski S et al., Predictability of individual circadian phase during daily routine for medical applications of circadian clocks. JCI Insight 2019.