Advancing data science in drug development through an innovative computational framework for data sharing and statistical analysis.

BACKGROUND: Novartis and the University of Oxford's Big Data Institute (BDI) have established a research alliance with the aim to improve health care and drug development by making it more efficient and targeted. Using a combination of the latest statistical machine learning technology with an innovative IT platform developed to manage large volumes of anonymised data from numerous data sources and types we plan to identify novel patterns with clinical relevance which cannot be detected by humans alone to identify phenotypes and early predictors of patient disease activity and progression. METHOD: The collaboration focuses on highly complex autoimmune diseases and develops a computational framework to assemble a research-ready dataset across numerous modalities. For the Multiple Sclerosis (MS) project, the collaboration has anonymised and integrated phase II to phase IV clinical and imaging trial data from ≈35,000 patients across all clinical phenotypes and collected in more than 2200 centres worldwide. For the "IL-17" project, the collaboration has anonymised and integrated clinical and imaging data from over 30 phase II and III Cosentyx clinical trials including more than 15,000 patients, suffering from four autoimmune disorders (Psoriasis, Axial Spondyloarthritis, Psoriatic arthritis (PsA) and Rheumatoid arthritis (RA)). RESULTS: A fundamental component of successful data analysis and the collaborative development of novel machine learning methods on these rich data sets has been the construction of a research informatics framework that can capture the data at regular intervals where images could be anonymised and integrated with the de-identified clinical data, quality controlled and compiled into a research-ready relational database which would then be available to multi-disciplinary analysts. The collaborative development from a group of software developers, data wranglers, statisticians, clinicians, and domain scientists across both organisations has been key. This framework is innovative, as it facilitates collaborative data management and makes a complicated clinical trial data set from a pharmaceutical company available to academic researchers who become associated with the project. CONCLUSIONS: An informatics framework has been developed to capture clinical trial data into a pipeline of anonymisation, quality control, data exploration, and subsequent integration into a database. Establishing this framework has been integral to the development of analytical tools.

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.

Actin filaments are required for fibripositor-mediated collagen fibril alignment in tendon.

Cells in tendon deposit parallel arrays of collagen fibrils to form a functional tissue, but how this is achieved is unknown. The cellular mechanism is thought to involve the formation of intracellular collagen fibrils within Golgi to plasma membrane carriers. This is facilitated by the intracellular processing of procollagen to collagen by members of the tolloid and ADAMTS families of enzymes. The carriers subsequently connect to the extracellular matrix via finger-like projections of the plasma membrane, known as fibripositors. In this study we have shown, using three-dimensional electron microscopy, the alignment of fibripositors with intracellular fibrils as well as an orientated cable of actin filaments lining the cytosolic face of a fibripositor. To demonstrate a specific role for the cytoskeleton in coordinating extracellular matrix assembly, cytochalasin was used to disassemble actin filaments and nocodazole or colchicine were used to disrupt microtubules. Microtubule disruption delayed procollagen transport through the secretory pathway, but fibripositor numbers were unaffected. Actin filament disassembly resulted in rapid loss of fibripositors and a subsequent disappearance of intracellular fibrils. Procollagen secretion or processing was not affected by cytochalasin treatment, but the parallelism of extracellular collagen fibrils was altered. In this case a significant proportion of collagen fibrils were found to no longer be orientated with the long axis of the tendon. The results suggest an important role for the actin cytoskeleton in the alignment and organization of the collagenous extracellular matrix in embryonic tendon.