Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition
of cancer clones (October 2024)
Authors: Aleksandr Ianevski, Kristen Nader, Kyriaki Driva, Wojciech Senkowski, Daria Bulanova, Lidia Moyano-Galceran, Tanja Ruokoranta, Heikki Kuusanmäki, Nemo Ikonen, Philipp Sergeev, Markus Vähä-Koskela, Anil K. Giri, Anna Vähärautio, Mika Kontro, Kimmo Porkka, Esa Pitkänen, Caroline A. Heckman, Krister Wennerberg & Tero Aittokallio
Article
Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a combinatorial challenge, since the number of possible drug-dose combinations vastly exceeds what could be tested in patient cells. Here, we describe a machine learning approach, scTherapy, which leverages single-cell transcriptomic profiles to prioritize multi-targeting treatment options for individual patients with hematological cancers or solid tumors. Patient-specific treatments reveal a wide spectrum of co-inhibitors of multiple biological pathways predicted for primary cells from heterogenous cohorts of patients with acute myeloid leukemia and high-grade serous ovarian carcinoma, each with unique resistance patterns and synergy mechanisms. Experimental validations confirm that 96% of the multi-targeting treatments exhibit selective efficacy or synergy, and 83% demonstrate low toxicity to normal cells, highlighting their potential for therapeutic efficacy and safety. In a pan-cancer analysis across five cancer types, 25% of the predicted treatments are shared among the patients of the same tumor type, while 19% of the treatments are patient-specific. Our approach provides a widely-applicable strategy to identify personalized treatment regimens that selectively co-inhibit malignant cells and avoid inhibition of non-cancerous cells, thereby increasing their likelihood for clinical success.
Attention-based approach to predict drug–target interactions across seven target superfamilies (August 2024)
Authors: Aron Schulman, Juho Rousu, Tero Aittokallio & Ziaurrehman Tanoli
Article
Drug–target interactions (DTIs) hold a pivotal role in drug repurposing and elucidation of drug mechanisms of action. While single-targeted drugs have demonstrated clinical success, they often exhibit limited efficacy against complex diseases, such as cancers, whose development and treatment is dependent on several biological processes. Therefore, a comprehensive understanding of primary, secondary and even inactive targets becomes essential in the quest for effective and safe treatments for cancer and other indications. The human proteome offers over a thousand druggable targets, yet most FDA-approved drugs bind to only a small fraction of these targets.This study introduces an attention-based method (called as MMAtt-DTA) to predict drug–target bioactivities across human proteins within seven superfamilies. We meticulously examined nine different descriptor sets to identify optimal signature descriptors for predicting novel DTIs. Our testing results demonstrated Spearman correlations exceeding 0.72 (P < 0.001) for six out of seven superfamilies. The proposed method outperformed fourteen state-of-the-art machine learning, deep learning and graph-based methods and maintained relatively high performance for most target superfamilies when tested with independent bioactivity data sources. We computationally validated 185 676 drug–target pairs from ChEMBL-V33 that were not available during model training, achieving a reasonable performance with Spearman correlation >0.57 (P < 0.001) for most superfamilies. This underscores the robustness of the proposed method for predicting novel DTIs. Finally, we applied our method to predict missing bioactivities among 3492 approved molecules in ChEMBL-V33, offering a valuable tool for advancing drug mechanism discovery and repurposing existing drugs for new indications.
RepurposeDrugs: an interactive web-portal and predictive platform for repurposing mono- and combination therapies (July 2024)
Authors: Aleksandr Ianevski, Aleksandr Kushnir, Kristen Nader, Mitro Miihkinen, Henri Xhaard, Tero Aittokallio & Ziaurrehman Tanoli
Article
RepurposeDrugs (https://repurposedrugs.org/) is a comprehensive web-portal that combines a unique drug indication database with a machine learning (ML) predictor to discover new drug-indication associations for approved as well as investigational mono and combination therapies. The platform provides detailed information on treatment status, disease indications and clinical trials across 25 indication categories, including neoplasms and cardiovascular conditions. The current version comprises 4314 compounds (approved, terminated or investigational) and 161 drug combinations linked to 1756 indications/conditions, totaling 28 148 drug–disease pairs. By leveraging data on both approved and failed indications, RepurposeDrugs provides ML-based predictions for the approval potential of new drug–disease indications, both for mono- and combinatorial therapies, demonstrating high predictive accuracy in cross-validation. The validity of the ML predictor is validated through a number of real-world case studies, demonstrating its predictive power to accurately identify repurposing candidates with a high likelihood of future approval. To our knowledge, RepurposeDrugs web-portal is the first integrative database and ML-based predictor for interactive exploration and prediction of both single-drug and combination approval likelihood across indications. Given its broad coverage of indication areas and therapeutic options, we expect it accelerates many future drug repurposing projects.
Exploring SureChEMBL from a drug discovery perspective (May 2024)
Authors: Yojana Gadiya, Simran Shetty, Martin Hoffmann-Apitius, Philip Gribbon & Andrea Zaliani
Article
In the pharmaceutical industry, the patent protection of drugs and medicines is accorded importance because of the high costs involved in the development of novel drugs. Over the years, researchers have analyzed patent documents to identify freedom-to-operate spaces for novel drug candidates. To assist this, several well-established public patent document data repositories have enabled automated methodologies for extracting information on therapeutic agents. In this study, we delve into one such publicly available patent database, SureChEMBL, which catalogues patent documents related to life sciences. Our exploration begins by identifying patent compounds across public chemical data resources, followed by pinpointing sections in patent documents where the chemical annotations were found. Next, we exhibit the potential of compounds to serve as drug candidates by evaluating their conformity to drug-likeness criteria. Lastly, we examine the drug development stage reported for these compounds to understand their clinical success. In summary, our investigation aims at providing a comprehensive overview of the patent compounds catalogued in SureChEMBL, assessing their relevance to pharmaceutical drug discovery.
Medical Management for Fracture Prevention in Children with Osteogenesis Imperfecta (March 2024)
Authors: Paul Arundel, Nick Bishop
Article
There are no licensed treatments for children with osteogenesis imperfecta. Children currently receive off-label treatment with bisphosphonates, without any consistent approach to dose, drug or route of administration. Meta-analyses suggest that anti-fracture efficacy of such interventions is equivocal. New therapies are undergoing clinical trials, and it is likely that one or more will receive marketing authorisation within the next three to five years. The long-term outcome from such interventions will need to be studied carefully well beyond the period over which the clinical trials are conducted, and a consistent approach to the collection of data in this regard will be needed as a major collaborative effort.
Drug Repurposing at Fraunhofer ITMP ScreeningPort (2024)
Authors: Maria Kuzikov, Jeanette Reinshagen, Johanna Huchting, Andrea Zaliani, Philip Gribbon
Poster
Drug repurposing plays a pivotal role in addressing the therapeutic gaps for rare and neglected diseases by leveraging existing medications for ew indications. This approach accelerates the drug development process, offering a cost‐effective and efficient way to repurpose established drugs to meet the urgent medical needs of populations often overlooked by traditional pharmaceutical research. Fraunhofer ITMP creates an accessible value chain of compound libraries, assays, life science informatic to enable scientist and industry to facilitate their drug repurposing projects.
Repurposing of Valproic Acid and Simvastatin to potentiate first line chemotherapy regimen in metastatic pancreatic cancer patients: from preclinical evidence to clinical testing in VESPA trial (2024)
Authors: Alfredo Budillon, Maria Serena Roca, Federica Iannelli, Veronica Barile, Rossella Migliorino, Eugenia Passaro, Cristina Testa, Laura Addi, Laura Grumetti, Tania Moccia, Carlo Vitagliano, Lucrezia Silvestro, Francesca Foschini, Carmine Carbone, Lorenzo Priori, Maddalena Fratelli, Laura Fiorenza, Maria Laura Garcia Bermejo, Bruno Sainz Jr, Francesca Bruzzese, Diana Giannarelli, Mercedes Rodriguez Garrote, Giampaolo Tortora, Michele Milella, Michele Reni, Elena Di Gennaro, Christine Kubiak, Eve Scott, Claudia Fuchs, Alessandra Leone, Antonio Avallone
Poster
Despite advances in cancer therapies, metastatic pancreatic ductal adenocarcinoma (mPDAC) patients have poor prognosis with median progression-free survival of the standard first-line gemcitabine/nab-paclitaxel-based chemotherapy (AG) not exceeding 7 months, suggesting the urgent need of novel treatments. We propose an innovative therapeutic strategy, based on the repurposing of valproic acid (VPA), an anticonvulsant with histone deacetylase inhibitor activity, and simvastatin (SIM), a generic cholesterol-lowering drug, in combination with AG. We tested antitumoral effects of VPA/SIM combination, alone or in association with chemotherapy in vitro in PDAC models demonstrating a strong synergistic anti-proliferative and pro-apoptotic effect of the combined treatment, in human and murine PDAC cells including patient-derived xenograft cells. Synergistic antitumor interaction was further observed as impairment of clonogenic capability as well as growth inhibition in 3D models, such as fibroblast/tumor cell microtissues and patient derived-organoids. Antitumor effect was confirmed in vivo on both heterotopic and orthotropic/metastatic xenograft PDAC models in nude mice. Transcriptomic analysis performed on tumor tissues from in vivo experiments revealed that VPA/SIM combination regulate several protumorigenic pathways through TGF-β and YAP signaling modulation as well as non-coding RNA. Overall, we proposed a novel and affordable combination therapy, based on two orally safe and generic drugs, to sensitize a widely employed first-line treatment in poor prognosis mPDAC patients, providing the rationale for investigating VPA/SIM plus AG-based chemotherapy in a multicentric randomized phase-2 study (VESPA trial; EudraCT 2022-004154-63; NCT05821556), that was launched in mPDAC with PFS as primary end-point. This trial, planned as patient-centric since the research design in collaboration with patients associations, is actively recruiting in Italian and Spanish centers.
AI Powers Drug Repurposing: Predicting Side Effects of Small Molecules (2024)
Authors: Filippo Lunghini, Anna Fava, Vincenzo Pisapia, Francesco Sacco, Daniela Iaconis, Carmine Talarico, Davide Graziani, Andrea Rosario Beccari
Poster
Repurposing refers to the identification of novel therapeutic applications for existing drugs, encompassing a range of common, challenging, and rare diseases. Conversely, polypharmacology entails the interaction of drug molecules with numerous targets across various therapeutic indications and diseases. Drugs exhibiting multi-targeting potential, hold significant appeal for repurposing, due to their ability to synergistically engage with multiple targets. In silico predictions are crucial for drug repurposing due to their ability to efficiently fill in sparse drug-targets annotations and suggesting new repurposing hypothesis. Herein we introduce ProfhEX, a suite of ligand-based AI-driven machine learning models for small molecules feature estimation, including PhysChem and ADME properties, multi-target interactions and potential liabilities. By leveraging a comprehensive knowledge base of >5M experimental data, ProfhEX currently predicts >30 ADME properties and drug-target interactions for >600 therapeutically relevant targets. The first version of ProfhEX, which focused on anticipating important liability profiles such as cardio-, neuro- and liver toxicities has already been published [1]. A further key feature of ProfhEX is the ability to identify potential metabolic pathway and automatically estimate drug’s most probable metabolites, enabling the evaluation of more complex polypharmacological interactions and therefore strengthen the discovery process. ProfhEX offers researchers a comprehensive tool to assess the safety and efficacy of potential drug candidates, and in the context of the R4ALL project, can can be a valuable tool for the correct in silico evaluation and characterization of drugs that could enter the drug repurposing process. The web application is free and reachable here: https://profhex.exscalate.eu/ [1] https://jcheminf.biomedcentral.com/articles/10.1186/s13321-023-00728-6
COVID-19 PATIENTS DERIVED LYMPHOBLASTOID CELL LINES AS AN ALTERNATIVE TO WHOLE BLOOD FOR COMPOUND SCREENING (2024)
Authors: Luka Hiti, Maša Kandušer, Tijana Markovič, Tilen Burnik, Mitja Lainščak, Emil Pal, Jerneja Farkaš Lainščak, Irena Mlinarič-Raščan
Poster
Cytokine storm, a COVID-19 complication, is a life-threatening systemic inflammatory syndrome involving the uncontrolled secretion of cytokines, which in severe cases leads to systemic organ failure and death. Especially in the first year of the COVID-19 pandemic, effective treatments for cytokine storm were not available. With the urgent need for treatment options, drug repurposing came to the forefront as it could cut the normal time from drug discovery to registration by more than two thirds. The first step in drug repurposing is compound screening, for which good in vitro cell models are necessary. We present here a novel in vitro cell model for evaluating the potential of compounds in decreasing the secretion of cytokines: immortalised B-lymphocytes, known as lymphoblastoid cell lines (LCLs). For drug screening we selected a set of compounds based on literature search or our previous research. We compared LCL to an established in vitro cytokine release model, whole blood. Whole blood represents phenotypes of different donors, contains different cell types, but it can only be used for one analysis and repeated sampling is needed. While there already are other commercial in vitro cell line models for cytokine secretion (e.g. THP-1, Jurkat), they represent only one phenotype. To cover different phenotypes, we have prepared a biobank of LCLs derived from 71 reconvalescent COVID-19 donors with differing severity of disease. Our results on a selected set of compounds indicate that the trend of cytokine secretion suppression is comparable between whole blood and LCL. The most promising results for drug repurposing were obtained for dexamethasone and MEK1/2 inhibitor trametinib. This supports the use of LCLs as a suitable in vitro cell model and as a good personalised medicine platform for cytokine-release related compound screening, since our LCL COVID-19 patients derived biobank accounts for interindividual differences.
In-depth exploration of assessment criteria for funding organizations involved in drug repurposing (2024)
Authors: Dalma Hosszú, Máté Pálfi, Zsuzsanna Petykó, Heleen van der Meer, Pan Pantziarka, Patricia Vandamme, Dunja Huijbers, András Inotai, Marcell Csanádi
Poster
Conventional valuation strategies for new medical entities are often not appropriate (do not capture all aspects of short and long-term value) to apply to drug repurposing, and there is a lack of broadly accepted methods for assigning quantifiable values to patient and societal benefit. REMEDI4ALL aims to create a range of incentives and funding opportunities to engage funders with drug repurposing (DR) projects. One key activity is to develop standardized assessment criteria for such projects. This will be in the form of a tailor-made and flexible tool that can encompass a wide range of assessment criteria more appropriate to the challenges of DR.
We performed a systematic overview of two major information sources: documents used by research funders (e.g. funding call application evaluation forms) and published literature. Potential funders were identified from the Funders Network, established by ZonMw within REMEDi4ALL. Such organizations were asked to share their relevant call documents, whether publicly or internally available. Scientific and grey literature were queried using PubMed and Google Scholar with additional publications made available from other REMEDi4ALL activities. An initial list of assessment criteria was created consisting of the raw texts selected from the queried data sources. Multiple criteria overlapped, differed in minor ways or were conceptually similar despite radically different wording. An iterative method was applied to group similar criteria together and to formulate concise and inclusive definitions in order to create a smaller fundamental set of assessment criteria. These were reformulated until a complete set of criteria that can conceptually include all the detailed collected data was established. Finally, based on the available data, a concise definition was attached to each criterion.
Exploiting real-world data to assist drug repurposing. Safety profiling of valproic acid and simvastatin combination treatment (2024)
Authors: Alessia Antonella Galbussera, Laura Fiorenza, Adrià Fernández-Torras, Jordi Quintana, Alessandra Leone, Alfredo Budillon, Mauro Tettamanti and Maddalena Fratelli
Poster
REMEDI4ALL is studying the repurposing of valproic acid (VPA) and simvastatin (SIM), administered on top of standard-of-care chemotherapy for metastatic pancreatic cancer. The two drugs are widely used and generally safe. However, we decided to evaluate the safety aspects of their combination using real-world data (RWD). We analyzed Lombardy Region’s administrative database (10M inhabitants). Healthcare in Italy is public, so the data are acquired for administrative and reimbursement purposes. Records contain information on sex, age, drug dispensation, hospital admissions together with primary and secondary diagnoses, ambulatory specialist visits and exemption registries. Subjects that acquired at least one package of VAL or SIM in 2015-21 without any package in the previous 5 years entered the cohort. More than 7,000 patients were treated with both drugs. Hospital admissions and outpatient visits showed no significant increase in these patients as compared to those in patients taking either drug individually. We also analyzed drug discontinuation rate, assuming that any side effects would lead to interruption of the treatment. The discontinuation rate of SIM was only slightly higher in patients with prior use of VAL than in those taking SIM only (HR 1.05, 95% CI 1.01-1.09). Conversely, there was a considerable decrease in the discontinuation rate of VAL in patients who were already taking SIM (HR 0.77, 95% CI 0.74-0.79). In parallel, we explored the post-marketing reports of adverse events (AEs) from four databases, which have been standardized, de-duplicated and corrected for masking effects in the CLARITY PV technology platform. Reassuringly, AE levels were generally lower in patients taking both VAL and SIM when compared to monotherapy, in agreement with the lower discontinuation rate observed in Lombardy. We conclude that there are no increased safety concerns in the patients taking both drugs. These results underline the importance of RWD in drug repurposing.
Engaging the patient community to ensure successful drug repurposing (2024)
Authors: Judit Baijet, Abby Stock-Duerdoth, Claudia Fuchs, Eve Hewitt, Virginie Hivert, William May, Rick Thompson
Poster
IDrug repurposing interest is steadily increasing in a variety of areas such as policy, regulation, funding and research. Although a huge amount of progress has been made in pushing forward this innovative opportunity in the drug development field, we frequently lack meaningful, efficient and effective patient centric perspectives to address unmet medical needs. REMEDi4ALL, the EU-funded multi-year initiative that aims at building a sustainable European innovation platform to enhance the repurposing of medicines for all, is positioning the patient’s voice and experience at the heart of every repurposing project and empowering them as true co-creators. To deliver on this mission, REMEDi4ALL is embedding patient engagement in all its four demonstrator projects as a core and essential principle for a patient-centric approach to drug repurposing. With the support of a dedicated and experienced patient engagement team established within the consortium, patient champions are identified and onboarded for every repurposing project to represent the patient community and make sure patients’ insights are taken into consideration. Similarly, patient advocacy groups are set up to support patient champions and to help shape the repurposing project for the benefit of the patient community. Through topic-specific multi-stakeholder meetings, REMEDi4ALL is also setting in a true collaborative environment bringing all stakeholders together to discuss different approaches to specific subjects on the drug development realm. REMEDi4ALL will also support patients and all the stakeholder groups with a comprehensive education and training portfolio designed to upskill, empower and build capacity among the whole drug repurposing ecosystem.
Challenges and solutions in the set-up of an international, cross-boundary, repurposing clinical trial for Osteogenesis Imperfecta (2024)
Authors: Judith Cohen, Mahboobeh Haji Sadeghi, Keith Pugh, Bronwen Williams, Sarah Sumpter, Francesca Gurioli, Maria Gnoli, Alice Moroni, Martina Piccini Leopardi, Clara del Coco, Luca Sangiorgi, Nicholas Bishop
Poster
The MOI-A demonstrator (10.4) project within the REMEDi4ALL Consortium is assessing the repurposing of losartan in adults and older adolescents with osteogenesis imperfecta, an inherited form of bone fragility, caused in the majority of cases by mutations in one of the two genes encoding type I collagen. We have encountered challenges due to the variation in regulatory processes across national boundaries. We report on these issues with the expectation that future studies will be able to proceed more swiftly. Sponsorship agreement: discussions covered whether to have one sponsor with a legal-representative in the partner country, but the final decision was to develop a co-sponsorship agreement. Protocol preparation and regulatory approval: we decided to use one master protocol across both countries ensuring that the same procedures for treatment and outcome measures are followed. Availability of the IMP: we were unable to source one product that could easily be supplied in both countries and decided to use two different products. We had to check that they had identical constituents and agree which of the SmPCs from the 2 different brands would be used as the reference safety information (RSI). Reporting of SUSARs approaches in both countries: to ensure that we can comply with pharmacovigilance guidance from the competent authorities we considered different approaches to reporting of SUSARs. The UK Sponsor will report all the study SUSARs to the MHRA and the Italian Sponsor will report all the study SUSARs to EVCTM/AIFA. Database arrangements: patients will be randomised from one central randomisation system, and data will be collected in one central database provided by the UK to enable streamlined study oversight. We will present the current status of each of these areas with details of the discussions between the study team, regulatory authorities and REMEDi4ALL research development team (RDT) and the eventual solutions.
Morphological profiling as a powerful approach for Drug Repurposing and disease modelling (2024)
Authors: Jordi Carreras-Puigvert, Martin Johansson, Malin Jarvius, Jonne Rietdijk, Polina Georgiev, Maris Lapins, Anders Larsson, Dan Rosén and Ola Spjuth
Poster
Phenotypic morphological profiling approaches, especially using Cell Painting, are gaining momentum as a powerful technology for compound profiling, mechanism of action (MoA) elucidation, safety, toxicology, disease modelling, and drug discovery. At the Pharmaceutical Bioinformatics (https://pharmb.io/) group at Uppsala University in Sweden, we have set up an automated lab and e-infrastructure to automatically perform Cell Painting and morphological profiling experiments. We combine phenomics (large scale morphological profiling), AI and automation for academic drug discovery, MoA prediction, as well as chemical and environmental toxicants profiling. In addition, as part of the Chemical Biology Consortium Sweden, we have profiled a drug repurposing library of 5270 annotated drugs and compounds that can be used for MoA investigation. Our lab has one of the largest morphological capacity and expertise in Europe and we strongly believe in the power of morphological profiling for drug repurposing, for which we are involved in several projects within REMEDI4ALL. We intend to continue exploring and profiling different disease models to be used in drug repurposing campaigns.
Attention-based approach to predict drug-target interactions across seven target superfamilies (2024)
Authors: Aron Schulman, Juho Rousu, Tero Aittokallio, Ziaurrehman Tanoli
Poster
Drug-target interactions (DTIs) hold pivotal role in drug repurposing and elucidation of drug mechanisms of action. While single-targeted drugs have demonstrated clinical success, they often exhibit limited efficacy against complex diseases, such as cancers, whose development and treatment is dependent on several biological processes. Therefore, a comprehensive understanding of primary, secondary and even inactive targets becomes essential in the quest for effective and safe treatments for cancer and other indications. The human proteome offers over a thousand druggable targets. Yet, most FDA-approved drugs bind with only a small fraction of disease targets. This study introduces an attention-based method to predict drug-target bioactivities for all human proteins across seven superfamilies. Nine different descriptor sets were meticulously examined to identify optimal signature descriptors for predicting novel DTIs. Our testing results demonstrated Spearman correlations exceeding 0.72 (P 0.57 (P<0.001) for most superfamilies. This justifies the robustness of the proposed method for predicting novel DTIs. Finally, we applied our method to predict missing activities among 3,492 approved molecules in ChEMBL-V33, offering a valuable tool for advancing drug mechanism discovery and repurposing existing drugs for new indications.
Exploring the morphology of host cells for innovative drug repurposing in viral infections (2024)
Authors: Marianna Tampere, AdelinnKalman, JonneRietdijk, Hanna Axelsson, Duncan Njenda,Elin Asp, Maris Lapins, Kun Qian, Flavio Ballante, Ola Spjuth, Jordi Carreras-Puigvert, Brinton Seashore-Ludlow and PäiviÖstling
Poster
Today, the majority of screening methods evaluate the drug activity on a given virus while neglecting the host mechanisms and responses to the virus infection. New approaches are hence needed to identify novel or repurposed drugs to treat deadly viral infections. Here, we have investigated the antiviral activity of 5200 compounds from the SPECS drug repurposing library using distinct screening campaigns on; 1) host cell morphology changes by the phenomics assay Cell Painting 2) specific antibody-detection of SARS-CoV-2 infection rate and 3) the current standard cytopathic effect method. We demonstrate how SARS-CoV-2 infection induced a specific phenotypic signature in Vero E6 cells, which was reversed by assay controls such as remdesivir. Our unbiased host-focused approach identified additional 324 compounds with antiviral activity against SARS-CoV-2. To further study the host response during infection, we quantified the subcellular localization and expression of 602 host proteins using antibodies from the Human Protein Atlas. We identified phenotypic responses to SARS-CoV-2 infection in 97 proteins. Finally, to broaden the paradigm of how antiviral therapies are identified we aim to combine these host-focused screening approaches. Our preliminary analyses have identified 3 host proteins linked to 3 compounds that reverse the virus-specific phenotype, which all represent novel drug repurposing candidates against SARS-CoV-2. Taken together, these findings illustrate a new host-centric approach for the discovery of antivirals and could be applied for other emerging or re-emerging viruses.
REMEDi4ALL Partners & Associated partners
