09:00 – 09:30 General Assembly – SDDN Association
09:30 – 10:00 Welcome and Presentation of the XV SDDN Meeting
10:00 – 10:30 Coffee Break
10:30 – 12:30 Session 1: The impact of AI-based tools and data science in Drug Discovery. Chair: Xavier Barril (Universidad de Barcelona).
Gianni De Fabritiis (Acellera and Universitat Pompeu Fabra), Barcelona, Spain
Robert Soliva (Almirall), Barcelona, Spain
Alfonso Rodríguez-Patón (Universidad Politécnica de Madrid, UPM), Madrid, Spain
Albert Antolin (Institut Català d’Oncologia (ICO)- IDIBELL), Barcelona, Spain
12:30 – 13:00 Presentations SDDN Partners and Event Sponsors I
13:15 – 14:15 Lunch
14:30 – 16:30 Session 2: Drug Discovery projects in public – private collaborations. Chair: Anabel Sanz (CRG).
Carmen Eibe (Pharmamar), Madrid, Spain
Mabel Loza (USC / Kaertor), Santiago de Compostela, Spain
Anji Miller (LifeArc), UK
José Miguel Vela (Welab), Barcelona, Spain
16:30 – 17:00 Presentations SDDN Partners and Event Sponsors II
17:00 – 17:30 Poster presentations (SLAS TonyB Award finalists)
17:30 – 19:30 Poster & networking session at exhibitors hall
(Coffee and refreshments)
20:30 Conference Dinner
09:00 – 11:00 Session 3: Using patient omics for the discovery of personalized medicines. Chair: Francesc Fernández (Almirall)
Javier Carmona (Hospital Vall D’Hebron), Barcelona, Spain
Alberto Santos (DTU Biosustain Research Center), Copenhagen, Denmark
Ricardo Gonzalo (Grifols), Barcelona, Spain
Maria Vinaixa (Universitat Rovira i Virgili, URV), Tarragona, Spain
11:00 – 11:45 Presentations SDDN Partners and Event Sponsors III
11:45 – 12:30 Poster & networking session at exhibitors hall
(Coffee and refreshments)
12:30 – 14:30 Session 4: Advanced Cell and Gene Therapies. Chair: Marjorie Pion (Health Research Institute Gregorio Marañón)
Jose Carlos Segovia (CIEMAT), Madrid, Spain
Juan Ruiz (Forge Biologics), Madrid, Spain
Antonio Pérez-Martinez (Hospital La Paz), Madrid, Spain
Rafael Correa (Health Research Institute Gregorio Marañón, IISGM), Madrid, Spain
14:30 – 15:00 Concluding remarks & announcement of SDDN 2024 meeting
15:00 – 16:00 Lunch
16:00-18:00 Additional networking
Machine Learning (ML) is a rapidly evolving technology that has penetrated our daily lives and all scientific disciplines. In the drug discovery arena, ML applications can be found at all stages of the process, from target identification to clinical trials, and has had (or will have) a disruptive effect on the daily operations of all scientists involved, starting with computational chemistry and structural biology, but rapidly moving to medicinal chemistry, biology and pharmacology. ML not only enables more efficient processes, but also affects how we generate usable and systematic data to feed those algorithms. In this session we aim to provide an overview of achievements, current directions, challenges and next frontiers in the field of ML applied to drug discovery. In particular, we aim to highlight three distinct areas of application:
Drug discovery can be performed by both private and public entities, and both have their own advantages and disadvantages. Their priorities and incentives are also different. In general, companies are better equipped and have better access to specialized resources, expertise, and funding. Companies focus is on moving promising drug candidates through the regulatory approval process and bring them to market, while public entities may be more interested in advancing basic research and understanding disease mechanisms, rather than in commercial purpose.
That being said, nowadays pharmaceutical have adopted new paradigms in the process of drug discovery thereby opening to collaborate with academic institutions, spin off and biotech companies with the aim to accelerate the drug development process, reduce costs, and increase the likelihood of success.
In turn, academic institutions and governmental agencies are making significant efforts to build capacities, technology platforms, and to fund early drug discovery projects that can efficiently transform innovative biomedical research into drugs to be further developed by the pharmaceutical industry.
The objective of this session is to present examples and capacities that leverage public-private collaboration to advance Drug Discovery.
There have been many important advancements in omics data generation technologies in recent years. These developments have led to the generation of large amounts of data that enables an unprecedent level of molecular characterisation of biological mechanisms. In this context, the integration of different types of patient-derived omics data provides insights into better understanding disease mechanisms, potentially identifying new drug targets and finally enabling the development of new personalized medicines. In this conference track, we will explore recent progress in using and integrating different flavours of patient-derived omics data for personalized medicine, with special focus on the challenges and opportunities associated with this rapidly evolving field.
Advanced cell and gene therapies (ACGTs) are medicinal products intended for human use that rely on genes, tissues, or cells. They provide revolutionary new opportunities for the treatment of diseases and injuries. ACGTs can be classified into three main types:
Gene therapy medicines designed to introduce recombinant genes into the body to achieve therapeutic, prophylactic, or diagnostic effects. In the field of genetic modifications, a broad range of techniques exists that may or may not directly modify the DNA, including but not limited to CRISPR/Cas9, ZF, AAV, and mRNA.
Somatic-cell therapy medicines contained cells or tissues that have been manipulated to alter their biological characteristics. They can be used to cure, diagnose, or prevent diseases.
Tissue-engineered medicines are composed of cells or tissues that have been modified to enable their use in the repair, regeneration, or replacement of human tissue.
In some cases, these therapies may include medical devices as an integral part of the medicine, which are referred to as combined ACGTs. For instance, cells embedded in a biodegradable matrix or extracellular vesicles.
Currently, the level of knowledge and technical advancement achieved make advanced therapies ideal for treating rare diseases or unmet medical needs. In this session we would like to introduce some recent advances in this field.