Background: Circadian timing of treatments can largely improve tolerability and efficacy in patients. Thus, drug metabolism and cell cycle are controlled by molecular clocks in each cell, and coordinated by the core body temperature 24-hour rhythm, which is generated by the hypothalamic pacemaker. Individual circadian phase is currently estimated with questionnaire-based chronotype, center-of-rest time, dim light melatonin onset (DLMO), or timing of CBT maximum (acrophase) or minimum (bathyphase).
Methods: We aimed at circadian phase determination and read-out during daily routine in volunteers stratified by sex and age. We measured (i) chronotype; (ii) q1min CBT using two electronic pills swallowed 24-hours apart; (iii) DLMO through hourly salivary samples from 18:00 to bedtime; (iv) q1min accelerations and surface temperature at anterior chest level for seven days, using a tele-transmitting sensor. Circadian phases were computed using cosinor and Hidden-Markov modelling. Multivariate regression identified the combination of biomarkers that best predicted core temperature circadian bathyphase.
Results: Amongst the 33 participants, individual circadian phases were spread over 5h10min (DLMO), 7h (CBT bathyphase) and 9h10 min (surface temperature acrophase). CBT bathyphase was accurately predicted, i.e. with an error <1h for 78.8% of the subjects, using a new digital health algorithm (INTime), combining time-invariant sex and chronotype score, with computed center-of-rest time and surface temperature bathyphase (adjusted R-squared = 0.637).
Conclusion: INTime provided a continuous and reliable circadian phase estimate in real time. This model helps integrate circadian clocks into precision medicine and will enable treatment timing personalisation following further validation
