2022/2023 Challenges
1. Provide an analysis of European clusters of innovation, both academia and industry, in the areas of areas of oncology, immuno-sciences, mitochondrial biology, or gene, cell and mRNA therapy.
2. Compare and contrast global pharmaceutical corporate venture capital functions. Including but not limited to: capital deployed, strategic vs financial, stage of investment, sector focus.
3. Due diligence of a specific project we are working on at the time. This would include scientific diligence and/or market and competitor analysis.
4. Join a major Pharma team and provide an overview of the landscape in a particular disease mechanism, filter and prioritise articulated opportunities to enable Business Development conversations to start with potential partners in Cambridge ecosystem.
5. Design an experimental protocol for unbiased screening to identify novel AAV capsid serotypes to enhance transduction of the retina following intravitreal injection.
6. Identify a set of potential differentiated targets for PROTACs based on assuming the degrader and the targeting moiety are separable.
7. Examine the antimicrobial resistance market and identify how new products can be generated and commercialised successfully.
8. Research and identify delivery models for autologous cell therapies for underserved markets, such as rural communities and low and middle income countries.
9. Scientific approaches to understanding the mechanisms of ageing and how they could translate to increased healthspan in humans. Elucidate the wide-ranging approaches to understand the mechanisms that underpin human ageing and explore how they could be therapeutically targeted or reprogrammed in order to age more healthily. Consider whether it is possible to identify unifying mechanisms or whether they are cell-, organ-, system- specific. Your research should also include the range of ageing models and a discussion on the relevance and translatability of these systems to human ageing.
10. How can cell health and resilience be measured? Consider what cell health means and explore whether a defined set of markers could be established, and how that might change with development or with cell type. Is a resilient cell a healthy cell? Explore and identify central mechanisms of cellular resilience and consider how this could be identified, assayed and whether it is feasible to make cells more resilient to the effects of ageing.
11. Map research that aims to understand the mechanisms of ageing across the local, UK and European research environments. While this should include the well-developed community of researchers with a clear ageing focus, you should also aim to identify and explore novel areas of biology that could be relevant to the understanding of human ageing. Your analysis should also take an interdisciplinary perspective, considering what we can learn from wider areas of science.
12. University origin research is increasingly generating data sets and data analysis that suggests the potential for early-stage diagnosis of medical conditions. Commonly, the disease conditions that are under investigation are those for which early diagnosis is critical for disease management or treatment or characterised is important and where early diagnosis is challenging; for example neurodegenerative disorders. Capitalising on the these insights and developing and implementing effective routes to market to give valuable patient benefit and a robust commercial proposition remains extremely difficult in most cases. The challenge is to develop novel business model (or models) that may overcome existing challenges and deliver good outcomes for patients and good commercial returns and that help inform researchers on how best to develop their technologies to place them well for commercial success.
13. Identify novel pathways driving pro-resolution responses in innate immune cells. Specifically, the identification and assessment of therapeutic targets and pathways that drive pro-resolution responses in innate immune cells that can be used to treat autoimmune and/or chronic inflammatory diseases. These include (but are not limited to) cessation of neutrophil tissue infiltration, counter-regulation of chemokines and cytokines, induction of apoptosis in spent neutrophils while promoting efferocytosis by macrophages, transformation from inflammatory to resolving macrophage phenotype, and the return of non-apoptotic immune cells to the vasculature or lymphatics.
14. What epigenomic features can add to our understanding of cancers, predict response to therapy and resistance mechanism? More specifically, many epigenomic features are available and can be profiled, including chromatin accessibility, DNA methylation, RNA methylation/modification, non-coding RNAs, global histone modification, site specific histone modifications (by CHIP-seq, or cut-and-run, or cut-and-tag). What epigenomic features are most relevant, and be combined with genomic and proteomic dataset to inform cancer treatment? Also, multiple technologies are available and emerging to profile different epigenomic features. How to prioritize what technologies to assay/profile different epigenomic features.
15. Develop new protocols and workflows to establish genome wide CRISPR KO scRNAseq to increase the number of KO genes– Currently we are limited to the low 100’s genes to KO before it becomes cost prohibitive.
16. Develop and produce a functional genomics data visualisation and interpretation platform that can integrate screening data with external databases. The purpose here is to integrate in a user-friendly manner the data coming from various external (and internal) databases for CRISPR screens with the intent of creating a “one stop shop” for the interpretation and the visualization of all of this knowledge.
17. Develop new protocols and workflows for ultra-miniaturisation for arrayed CRISPR screening (above 384 well plates).
18. Develop new protocols to deliver CRISPR reagents at scale (e.g.384 well plate settings) in hard to transfect cell types (e.g. primary cells such as lung epithelial cells, immune cells, cardiomyocytes, iPSC cells, etc) to enable high fidelity genome wide arrayed CRISPR screening.
19. Emerging screening modalities and read outs (including scOMICS technologies) to enable discovery and validation of novel lncRNA as drug targets. The intent here is to create a new screening and bioinformatic pipeline that enables us to identify and validate novel drug targets that come from the non-coding genome (including lncRNA). At the moment all workflows, experimental and bioinformatic pipelines are aimed at discovering targets coming from the coding genome which however represents only 1% of the human genome. There is a big untapped opportunity to discover novel targets and generate new biological insights.
20. Work with a leading venture capital investor backing and building category-leading deep tech and life sciences companies. Assignments include identifying and assessing market trends across the life sciences sector, conducting technical and market due diligence, and gaining exposure to the venture capital investment process.
21. There are now multiple methods of collecting and assimilating disease related data at cellular, organoid and population levels. Associations are readily derived in GoF and LoF genetic variants, proteomics and multi-omic expression, effects of splice variants, epigenetic states associated with readers, writers and erasers. The list goes on, each individual proponent points to their technique holding the golden key. There is a gap though in genuinely collating these data and pointing to the causal point of intervention in disease amongst all these data. Techniques to rapidly identify the causal points of interference are needed which can be orthogonally and reliably wet tested.
22. Federated Learning (FL) enables machine learning (including algorithm training and statistical analysis) using data from multiple distributed Data Providers while enabling data to remain in the Data Providers’ custody. Published cases of FL in Health and Life Sciences have validated that federation of model results is effective compared to other collaboration approaches:
- Federated learning in medicine
- Collaborative Federated Learning For Healthcare
- Federated Learning for Predicting Clinical Outcomes in Patients
Given that FL enables Data Providers to retain continuous custody of their own data, it has been presumed that it provides sufficient data security for data sets that have hitherto been unavailable due to Data Protection concerns. However, there appears not to be literature validating the data security of the approach: whether it is possible to reconstruct data from model results or whether there are unforeseen Privacy & Security risks. As we explore FL opportunities in Life Sciences, we have the following questions:
What near term opportunities are opened up by FL in Life Sciences? What are the most meaningful near term use cases from a scientific discovery or commercial perspective?
What are the Data Protection risks of FL and how would we certify to potential Data Providers that a FL platform is secure?
Are there gold standards in data security and privacy in other industry sectors or data sharing technologies that could form the basis of a new standard here?
23. Novel therapies for neuropsychiatric disorders are being developed that target biologically distinct patient subgroups. Potential data for patient stratification in the future may include symptoms, genetics or other biological measurements, EEG, digital measures including gamified cognitive tests, or combinations of these. Real world data available today, including EHR and claims data is not sufficiently detailed to identify these patient subgroups, and thus do not fully empower precision medicine strategies. The ability to find patient subgroups in real world data would enable quantification of unmet need, efficient recruitment for clinical trials, or development of external control arms. Provide an analysis and proposals for opportunities to partner and create real world data with the ability to generate “at scale” data that enables patient stratification based on the above measurement domains.
24. Success against Alzheimer’s disease will likely require early interception of disease, potentially prior to signs of cognitive decline. Evaluate opportunities and propose approaches for the identification of subjects who are likely to have pathological hallmarks of Alzheimer’s disease but are cognitively normal, using low-friction technologies that could be administered in a patient’s home.
25. To realize a precision medicine strategy for neuropsychiatric disorders, dissecting different types of alterations to the function of neural circuits will be important. One approach to quantifying the performance of different aspects of neural computation is through cognitive tests. Provide an evaluation of domains that cut across psychiatric disorders (e.g. anxiety, anhedonia, …), the availability of app based tests across these domains, and propose a study quantifying patient subgroups leveraging a suite of tests.
26. Provide insight and identify translational models within lysosomal biology. Provide a deep dive into experimental models that can be translated between preclinical and clinical studies which assess lysosomal function and protein aggregation (both in vitro and in vivo). Explore possible biomarkers in the lysosomal area that can be utilized to build a framework for precision medicine in neurodegenerative disorders.
27. Biomacromolecules, such as antibodies, oligonucleotides and peptides, have transformed our capacity to effectively treat disease but administration is limited to parenteral routes only. Needle phobia affects 20% to 30% of adults (20 – 40y), impacting patient acceptance and compliance which results in worse outcomes for these patients. Oral administration could increase patient adherence, compliance and acceptance as well as removing the need for complicated parenteral administrations that often require either a visit to a clinic or a home visit from a healthcare professional. Therefore, safe solutions to overcome both degradation and poor absorption in the GI tract, which thereby enable oral delivery of biomacromolecules with bioavailability comparable to parenteral administration, is a key challenge which we seek support to address.