A Virtual Physiological Human model of the menstrual cycle and the growing follicles for in silico clinical trials
Paeon VPH Model is the Virtual Physiological Human (VPH) model developed within Paeon.
It is a mathematical model defining the time evolution of the hormones playing a role in the human menstrual cycle and of the follicles growing in the ovaries.
Paeon VPH Model is at the core of most of the Paeon technology and is a key enabler of in silico clinical trials.
Paeon VPH Model is a mathematical model based on differential equations and has been designed starting from the qualitative biological knowledge of the physiology of the human menstrual cycle and the effects of fertility drugs.
The model has been tuned and validated exploiting large amounts of retrospective clinical data to ensure that it reliably mimics the natural behaviour, both with and without administration of fertility drugs.
Paeon VPH Model contains many parameters. Different values to these parameters yield different model behaviours and capture the physiological differences among different women for what concerns their menstrual cycle, growth of follicles, and reaction to fertility drugs.
Different assignments of values to model parameters define different Virtual Patients, who in turn model distinct classes of real patients.
From the Paeon VPH Model we have computed 20k+ Virtual Patients, each one representing a clearly distinct natural behaviour of the menstrual cycle and the growing follicles, with and without administrations of fertility drugs.
This population of virtual patients enables in silico clinical trials of fertility treatments.
The figure shows the regulatory network modelling the human physiology mechanisms behind the menstrual cycle, that it the chemical reactions and stimulatory and inhibitory effects through biological species (hormones concentrations, receptor complexes, etc.)
The cycle begins in the hypothalamus, where Gonadotropin-releasing Hormone (GnRH) is produced. This hormone reaches the pituitary gland and stimulates release of Luteinizing Hormone (LH) and Follicle Stimulating Hormone (FSH), the most important hormones that regulate, in the ovaries, the follicular growth, the ovulation process and the development of Corpus Luteum.
During their growth, follicles synthesise Estradiol (E2) and, later, Progesterone (P4). These hormones reach the hypothalamus and influence the production of GnRH, LH and FSH.
Paeon VPH Model is defined by a system of differential equations.
Each differential equation defines the behaviour of a biological species having a role in the human menstrual cycle.
Equations depend on various parameters, whose values take into account inter-patient variability of the menstrual cycle, follicular growth and reaction to fertility drugs.
Parameters of the Paeon VPH Model have been tuned by exploiting solid mathematical optimisation methods (Gauss-Newton) and available clinical measurements of healthy women.
The goal of such a tuning phase was get a Standard Virtual Patient, that is a model behaviour which could be regarded as 'physiologically correct'.
The figure shows the time evolution of the Standard Virtual Patient as for what concerns the 4 most important hormones (E2, P4, FSH, LH) involved in the menstrual cycle, together with the clinical measurements (on healthy real patients) exploited during the tuning phase (red dots).
Our Standard Virtual Patient clearly shows a physiologically correct behaviour, in that it averages the behaviours of the real patients used during the tuning phase. The behaviour of our Standard Virtual Patient also matches current medical knowledge, as described in the specialised literature.
The Standard Virtual Patient has been used as a starting point to build an entire population of virtual patients, each one representing a different class of real patients. The availability of such population is a key enabler for in silico clinical trials.
We built our population of Virtual Patients by exploiting sophisticated computational methods (Statistical Model Checking) which intelligently explore the space of the Paeon VPH Model parameters searching for parameter values which entail time evolutions (for all the biological species) qualitatively similar to those of the Standard Virtual Patient.
Our population consists of 20k+ Virtual Patients, who are in agreement with medical knowledge and available clinical data.
The figure shows the time evolution (for what concerns the 4 main hormones: E2, P4, FSH, LH) of the Standard Virtual Patient (dark curves) and of all Virtual Patients in our computed population (light curves). Red dots show the clinical measurements used for validation, as obtained by Pfizer and University Hospital Lausanne from 50+ healthy women and kindly provided to Paeon.