Trevor Mundel – Health Equity: One Simulation at a Time
Cheaper data processing capacity and a growing number of open source tools are creating an opportunity for Africa to adopt revolutionary new approaches to measuring the safety and efficacy of essential health interventions in African populations. Dr. Mundel will focus on four areas where African researchers are creating opportunities for the continent to leapfrog to more affordable and accessible pharmacometric technologies, including:
- Pharmacogenetics via the work of Human Heredity and Health in Africa (H3Africa) and the integrated drug discovery work of H3D;
- Clinical trial simulations to identify the most predictive indicators for evaluating the safety and efficacy of new therapeutics and new tools to address regulatory capacity gaps;
- Pan-African pharmacovigilance to ensure the safe scaling of new interventions to a broad population and to inform future product development priorities; and
- A comprehensive learning system that integrates data on diagnosis, delivery, and outcomes into a highly powered platform capable of driving health system innovation.
Dr. Mundel will also explore how partners across governments, philanthropies, and the private sector can work together to strengthen the science of pharmacometrics in Africa.
Jeanine Condo – The use of mass campaign to fight against NCDs in LMICs: case of Rwanda
For the past decades, non-communicable diseases (NCDs) have been neglected despite its contribution to cause of death in Africa. Nearly half of the population in this region already suffer from hypertension, a well-established precursor to NCDs such as heart attacks and strokes. NCDs have become the principal cause of morbidity, mortality and disability affecting the quality of life of patients suffering from NCDs. Unfortunately, patients with NCDs present themselves at a late-stage of clinical symptoms after impairment of key organs.
Access to a comprehensive quality of care is not only expensive but also unavailable in countries with limited resources. Rwanda has employed unconventional methods such as the healthy mass campaign “Car Free Day “ that simultaneously fights NCDs and air pollution.
Prof Condo Jeanine will use this program to highlight practical lessons learnt from collaborative efforts to address Africa’s disease burden.
Lena Friberg – Less is more? The tale of a myelosuppression model
One of the most cited pharmacokinetic-pharmacodynamic models in the literature is the “semi-physiological model of myelosuppression”, originally developed to describe the time-course of total white blood cells after chemotherapy treatment. The model was established with the idea of being general and parsimonious, with few parameters, rather than a ‘perfect’ model for one particular dataset. Nearly 20 years later, it is still a common building block to describe changes in blood cell counts over time.
The presentation will cover
- the story of the emergence of the model
- applications and ’add-ons’ – other blood cells, rescue treatment, other disease areas
- its use in drug development
- potential value for dose individualization
- connections to other PD-models and
- ‘tips and tricks’, including common misconceptions
Dr Friberg will also discuss the integration of the model in ‘frameworks’ that integrates various models for other adverse effects, tumor size, febrile neutropenia and survival of value for exploring dosages. cometric community.
Rada Savic – Development of Computational and Translational Tools for Drug Development of Combinational Regimens for Treatment of Tuberculosis
Recent TB drug discovery and development successes have delivered a number of new drug approvals, late stage drug candidates and repurposed antibiotics (https://www.newtbdrugs.org/pipeline/clinical), leaving the TB community with a good problem to have: with too many possible combinations, how do we prioritize new regimens for testing in resource and cost intensive clinical trials?
Given the complexity of human TB disease pathology and pathogen physiology, whether regimen ranking in any preclinical model systematically and quantitatively holds true in patients is often questioned. Indeed, predicting the clinical potential of regimens that are made of 3 or 4 antibiotics is challenging for several reasons. First, different bacterial populations are differentially susceptible to each antibiotic, and the relative representation of these populations is hardly recapitulated in mouse models. Second, the kinetics of drug penetration at the sites of disease is affected by lesion structure, which again differs between mice and men. Third, drug pharmacokinetics and drug-drug interactions are species specific, and human-equivalent doses of preclinical development candidates cannot be accurately achieved in the mouse. Lastly, the definitions of clinical endpoints and biomarkers of drug response are distinct in preclinical and clinical studies, which poses another challenge for accurate translation. Each of these challenges represents a potential obstacle for successful regimen development, and none of them exists in silo; they are all inter-related. Rather than insufficient data, the largest gap for successful regimen development is knowledge integration across all of these challenges and a deep understanding of how they inter-relate and quantitatively translate into the common goal, which is a relapse-free cure for all patients following short course treatment.
To that end, we integrated vast of drug development data ranging from preclinical studies in mice and rabbit, and clinical (Pharmacokinetic, Pharmacodynamic, biomarker and clinical outcome) data from Phase 2A, 2B and phase 3 trials including >10 distinct drugs. Based on this database, we develop set of translational and predictive models/tools that can ensure successful drug development and selection of the best combinations. The tools include empirical machine learning algorithms, mechanistic PKPD models, systems pharmacology/immunology model as well as integrative biomarker/clinical outcome relationships. Next, we propose novel early and late stage clinical trial designs and adaptive platform that can be used for drug regimen optimization linked to an in silico clinical trial simulation tool.