Periodic Reporting for period 4 - STriTuVaD (In Silico Trial for Tuberculosis Vaccine Development)
Berichtszeitraum: 2022-02-01 bis 2023-01-31
Tuberculosis (TB) one of the world’s deadliest diseases: one third of the world’s population, mostly in developing countries, is infected with TB. But TB is becoming again very dangerous also for developed countries, due to the increased mobility of the world population, and the appearance of several new bacterial strains that are multi-drug resistant (MDR). There is now a growing awareness that TB can be effectively fought only working globally, starting from countries like India, where the infection is endemic. Once a person present the active disease, the most critical issue is the current duration of the therapy, because of the high costs it involved, the increased chances of non-compliance (which increase the probability of developing an MDR strain), and the time the patient is still infectious to others. One exciting possibility to shorten the duration of the therapy are new host-reaction therapies (HRT) as a coadjuvant of the antibiotic therapy. The endpoints in the clinical trials for HRTs are time to sputum culture conversion, and incidence of recurrence. While for the first it is in some cases possible to have a statistically powered evidence for efficacy in a phase II clinical trial, recurrence almost always require a phase III clinical trial with thousands of patients involved, and huge costs.
In the STriTuVaD multidisciplinary consortium we will test, through phase IIb clinical trials, one of the most advanced therapeutic vaccines against DS-TB and MDR-TB i.e. RUTI vaccine, provided by Archivel Farma S.L (Spain).
In parallel we will extend the Universal Immune System Simulator to include all relevant determinants of such clinical trial, establish its predictive accuracy against the individual patients recruited in the trial, use it to generate virtual patients and predict their response to the HRT being tested, and combine them to the observations made on physical patients using a new in silico-augmented clinical trial approach that uses a Bayesian adaptive design. This approach, where found effective could drastically reduce the cost of innovation in this critical sector of public healthcare.
To achieve such important goal, we intend to reach the following objectives:
• Assessment of the computational modelling framework to simulate the human immune system complex dynamics at large scale;
• Development and integration into the general modelling framework of the module featuring the simulation of the TB – immune system interaction;
• Development and integration into the general modelling framework of the module featuring the simulation of the effects of antibiotics therapy in TB patients;
• Development and integration into the general modelling framework of the module featuring the simulation of the immunity induced by the TB vaccines;
• Set-up the library of virtual patients using data of real patients enrolled for the clinical trial and run an empowered in silico-augmented adaptive Bayesian clinical trial.
• In silico trial framework release by means of the validation of the real phase IIb clinical trial.
In the STriTuVaD multidisciplinary consortium we will test, through phase IIb clinical trials, one of the most advanced therapeutic vaccines against DS-TB and MDR-TB i.e. RUTI vaccine, provided by Archivel Farma S.L (Spain).
In parallel we will extend the Universal Immune System Simulator to include all relevant determinants of such clinical trial, establish its predictive accuracy against the individual patients recruited in the trial, use it to generate virtual patients and predict their response to the HRT being tested, and combine them to the observations made on physical patients using a new in silico-augmented clinical trial approach that uses a Bayesian adaptive design. This approach, where found effective could drastically reduce the cost of innovation in this critical sector of public healthcare.
To achieve such important goal, we intend to reach the following objectives:
• Assessment of the computational modelling framework to simulate the human immune system complex dynamics at large scale;
• Development and integration into the general modelling framework of the module featuring the simulation of the TB – immune system interaction;
• Development and integration into the general modelling framework of the module featuring the simulation of the effects of antibiotics therapy in TB patients;
• Development and integration into the general modelling framework of the module featuring the simulation of the immunity induced by the TB vaccines;
• Set-up the library of virtual patients using data of real patients enrolled for the clinical trial and run an empowered in silico-augmented adaptive Bayesian clinical trial.
• In silico trial framework release by means of the validation of the real phase IIb clinical trial.
The STriTuVaD consortium has set-up an effective management and governance structure, which ensured the progress of the project to reach its planned objectives and guaranteed the timeline performance of the work. Regular flow of communication with European Commission Officers have been performed and all the partners have been constantly informed in a timely and transparent manner through regular meetings.
The STriTuVaD consortium achieved the assessment of pre-existing modelling framework (UISS – Universal Immune System Simulator) to reproduce the human immune system dynamics at a large scale. Then, UISS modelling framework has been extended to simulate TB – immune system interactions. This allowed the simulations of artificial immunity induced by vaccinations and treatments for tuberculosis. As an initial step, it has been developed a detailed description of the UISS-TB model, including its mathematical formulation, which will be essential to formalise the credibility of such model. Finally the creation of libraries of virtual subjects and libraries of virtual vaccinated patients was the final step to reach a milestone i.e. the delivery of the computational modelling framework of personalized TB-treatments-host immune system interactions and dynamics.
Moreover, the consortium has developed a Bayesian model that provides a principled way of controlling the amount of information allowed into the augmented clinical trial, effectively enabling an in silico augmented clinical trial. Hierarchical generalised linear (hGLM) models for the main endpoint from either the in silico or in vivo data proposed for sharing information, include a component measuring the compatibility of in silico with in vivo patients, which comprise both technical and biological variability.
Archivel Farma completed the manufacturing and testing of the clinical batch of RUTI vaccine; Regulatory and Ethical committees approvals are achieved. A total of 111 TB patients have been enrolled till January 2023 and the DS cohort has completed the follow-up (no serious adverse events were been reported).
In the context of Covid-19, the UISS computational model has been extended to reproduce the dynamics of SARS-CoV-2 infection. We have tested the computational model to predict the results of the trained immunity after the vaccination of already marketed vaccines (such as DTP). The results showed that DTP holds the premise to potentially protect by SARS-CoV-2 under particular conditions.
The STriTuVaD in silico trial platform has been released as a Software as A Service through the STriTuVaD website (https://www.strituvad.eu/uiss-tb-simulator).
The STriTuVaD consortium achieved the assessment of pre-existing modelling framework (UISS – Universal Immune System Simulator) to reproduce the human immune system dynamics at a large scale. Then, UISS modelling framework has been extended to simulate TB – immune system interactions. This allowed the simulations of artificial immunity induced by vaccinations and treatments for tuberculosis. As an initial step, it has been developed a detailed description of the UISS-TB model, including its mathematical formulation, which will be essential to formalise the credibility of such model. Finally the creation of libraries of virtual subjects and libraries of virtual vaccinated patients was the final step to reach a milestone i.e. the delivery of the computational modelling framework of personalized TB-treatments-host immune system interactions and dynamics.
Moreover, the consortium has developed a Bayesian model that provides a principled way of controlling the amount of information allowed into the augmented clinical trial, effectively enabling an in silico augmented clinical trial. Hierarchical generalised linear (hGLM) models for the main endpoint from either the in silico or in vivo data proposed for sharing information, include a component measuring the compatibility of in silico with in vivo patients, which comprise both technical and biological variability.
Archivel Farma completed the manufacturing and testing of the clinical batch of RUTI vaccine; Regulatory and Ethical committees approvals are achieved. A total of 111 TB patients have been enrolled till January 2023 and the DS cohort has completed the follow-up (no serious adverse events were been reported).
In the context of Covid-19, the UISS computational model has been extended to reproduce the dynamics of SARS-CoV-2 infection. We have tested the computational model to predict the results of the trained immunity after the vaccination of already marketed vaccines (such as DTP). The results showed that DTP holds the premise to potentially protect by SARS-CoV-2 under particular conditions.
The STriTuVaD in silico trial platform has been released as a Software as A Service through the STriTuVaD website (https://www.strituvad.eu/uiss-tb-simulator).
UISS-TB, the computational framework developed by STriTuVaD, will deliver an effective integrated infrastructure able to predict the outcome of Clinical trial applied to the Tuberculosis field, reducing the number of patients and the time to market. The final product of the STriTuVaD project can be used to analyse and predict the effect of any treatments in patients affected by a particular strain of M. tb. STriTuVaD is progressing the state of the art setting a standard to the design and implementation of in silico trials for vaccines.
In particular, STriTuVaD project strongly impacts society and well-being providing:
- A reduction on the size and the duration of the human TB clinical trials. STriTuVaD computational framework offers an effective way to estimate time to inactivation of M.tb with a standard phase II clinical trial. UISS-TB can be used as a conclusive evidence and as a partial replacement of the phase III clinical trial, including a mean to increase the confidence in investing in a phase III trial to demonstrate the efficacy in term of reduced recurrence.
- A more effective human clinical trials design, through the adjustment of the dosage and the timing of the treatments to maximize the chances of success.
- Lower development costs and/or shorter time-to-market for new tuberculosis treatments. The simulation platform significantly lowers the costs associated with the execution of clinical trial. This has an incredible economic social impact for the low-income high tuberculosis burden countries.
- Pushing the regulatory evaluation for in silico trials through benchmarking approaches to validation/qualification of modeling and simulation frameworks.
In particular, STriTuVaD project strongly impacts society and well-being providing:
- A reduction on the size and the duration of the human TB clinical trials. STriTuVaD computational framework offers an effective way to estimate time to inactivation of M.tb with a standard phase II clinical trial. UISS-TB can be used as a conclusive evidence and as a partial replacement of the phase III clinical trial, including a mean to increase the confidence in investing in a phase III trial to demonstrate the efficacy in term of reduced recurrence.
- A more effective human clinical trials design, through the adjustment of the dosage and the timing of the treatments to maximize the chances of success.
- Lower development costs and/or shorter time-to-market for new tuberculosis treatments. The simulation platform significantly lowers the costs associated with the execution of clinical trial. This has an incredible economic social impact for the low-income high tuberculosis burden countries.
- Pushing the regulatory evaluation for in silico trials through benchmarking approaches to validation/qualification of modeling and simulation frameworks.