Dr Alexander Henzing

Transcription

1 Horizon 2020 Health, Demographic Change & Wellbeing EU funding, research and collaboration opportunities for 2016/17 Innovate UK funding opportunities in omics, bridging health and life sciences Dr Alexander Henzing

2 Innovate UK Funding To stimulate and support business-led innovation Accelerating UK economic growth Often collaborative projects Applied R&D funding rates: Up to 50% for large companies Up to 60% for SMEs 100% (80% FEC) for research institutes One or two stage application process

3 2015 Competitions (April) Developing non-animal technologies Biological, tissue engineering and imagingrelated Stem cell technologies/tissue engineering Next-generation sequencing and omics Stratified (personalised) medicine approaches Technologies for identifying and measuring in vitro biomarkers Computational and mathematical methods Mathematical modelling Computer simulation and in silico modelling Structure-activity relationships and computational chemistry Data-mining and analysis of large complex (including historical) data sets

4 2015 Competitions (July) Finding value in complex biological data integrated omics Scope: Innovative, integrated approaches which can demonstrate complex biological systems at the system level and help to de-risk development Looking for projects that develop innovative approaches using currently existing data as well as seeking novel approaches to building new tools, techniques and services

5 2015 Competitions Finding value in complex biological data integrated omics Examples of projects Tools and services to speed development of bio-products Analytical or diagnostic tools that look at multiple parameters in a discrete complex biological system Predictive biological system models in silico Evidence based models that demonstrate the impact on a biological system by introducing new candidate compounds and interventions Data analysis platforms tailored to omics and complex biological data streams

6 2015 Competitions (September) Technology-inspired Innovation Characterisation and discovery tools Commercial application of sequencing technologies focusing on genomics Integration and exploitation of phenotyping technologies Integration of omics technologies, such as integrating metabolomic, proteomic, genomic and phenomic data collection and interpretation capabilities Biological imaging systems, biosensors, probes/markers, diagnostic platforms

7 2015 Competitions (October) Analytical technologies for biopharmaceuticals Quality by Design (QbD) QbD promotes a more rational and scientific approach to the development and manufacture of biopharmaceuticals. Its purpose is to ensure quality is built in rather than tested in. Examples of analytical tools to support QbD approaches include: high-throughput tools and technologies to generate data and support multivariate data analysis during process development tools for multiplexed analysis of complex protein analytes or process- related impurities informatics tools to analyse complex multivariate datasets

8 2015 Competitions (October) Analytical technologies for biopharmaceuticals Improved in silico prediction of product characteristics Examples include: improved predictive in silico tools for assessing product structure, stability, potency or ease of manufacturing validation of new or existing in silico tools to confirm applicability to product development and manufacture

9 2015 Competitions (November) New modelling systems for stratified medicine Advance a product for a stratified approach to treatment, requiring the use of new modelling systems Integrate healthcare and science data, to predict the likelihood of a product demonstrating the intended effect or value in a clinical setting, incorporating approaches such as systems biology or bioinformatics Provide innovative multi-parameter algorithms that enhance the predictive strength of a diagnostic test and allow commercialisation Provide innovative healtheconomic models for products that will establish new clinical care pathways and allow product adoption

10 2015 Competitions (December) Stratified medicine: connecting the UK infrastructure Projects that seek to develop tests capable of classifying patients into groups and selecting them for a clinical treatment (or treatments) currently available in the UK. The term test is being used in the broadest sense and includes in-vitro and in-vivo diagnostic tests, physical measurements and the use of data to provide medical intelligence and guide clinical decisions. Tests carried out in hospitals, clinics, GP surgeries and the community are all in scope.

11 CRACK IT Challenges Metaboderm: Development of a new tool to predict metabolism in human skin Identify studies and test systems to investigate the skin metabolism of topically applied xenobiotics (in vitro/minimally invasive in human). Establish suitable analytical techniques for measurement of metabolites. Use of modelling to provide a kinetic understanding of the extent to which metabolism determines xenobiotic availability in skin. InMutaGene: Development of a technology to address the risks of insertional mutagenesis and oncogenesis and to improve translational research in gene therapy Evaluate the impact of diverse target cell lineages, level of differentiation, disease background and in vitro manipulation and expansion on vector integration profiles. Provide information to evaluate the predictive value of the non-clinical test developed.

12 UK Bioinformatics Landscape Big data & Data management Scope and scale of data generation, particularly in omics area resulting in research moving from hypothesis-driven to data-driven approach Data integration ( variety) Datamining (vs datawarehousing) Legacy data, data silos Data curation (annotation) Standards, semantics, ontologies Knowledge bases/knowledge management Data Visualisation Analysis tools for various data formats Analytics (data-science)

13 UK Bioinformatics Landscape Genome-scale in-silico modeling Genome-scale models can predict engineering strategies to enhance properties of interest in an organism and can provide a basis for rational engineering and synthetic biology in industrial and medical biotechnology Predict system-wide effect of genetic & environmental pertubations Integration of omic data (transcriptomics, proteomic, metabolomic) Metabolic Signalling Reduction in batch to batch variation Prediction (e.g. glycosylation for vaccine production)

14 UK Bioinformatics Landscape In-silico toxicity prediction Regulatory Drive (legislation in the European Union: Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), to help to reduce, refine and replace animal testing Physicochemical property & biological activity prediction Methodology Structure-Activity Relationships (SARs) Quantitative Structure Activity Relationships (QSARs) chemical grouping and read-across absorption, distribution, metabolism and elimination (ADME) Combinations of the above

15 UK Bioinformatics Landscape Data visualisation Exploratory data analysis Interactive, design usability, fit-for-purpose Extract biological meaning from complex data Insights leading to hypotheses Tighter coupling between analysis and visualisation More interaction with visualisations (of larger data) Parallelisation of algorithms and visualisations Pre-computation of large data sets (save time in later discovery steps

16 UK Bioinformatics Landscape Process modeling Predictive behaviour proteins (solubility, aggregation, media etc.) Whole system models (rational design) Modeling/prediction secondary & tertiary structure Properties Interaction (protein-protein, protein-small molecule) Molecular dynamics (affinity) Screening (develop analytics methods) Formulation Targets Scale down (rather than up) Getting from: data Learn/interpretation/drivers predictive models

17 Bioscience Strategy 2016 Omics, modeling and systems Multilayered in silico systems for replicating and predicting biological activity Intuitive user experience systems for complex biological data streams Modeling, design and workflow automation systems

18 The Knowledge Transfer Network Enabling Collaboration Strategic Interdisciplinary Entrepreneurial Commercial Dr Alexander Henzing