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Pharma & Biomarker Discovery Applications

Pharma & Biomarker Discovery Applications

We provide you with clinical data and bioinformatics solutions for translational and clinical research.

Curation of Public Datasets Generation of Multi-omics Datasets for Target Discovery Building Custom Bioinformatics Pipelines
01/ Curation

Curation of Public Datasets

Strand’s multidisciplinary team of curators, bioinformaticians, and data engineers has deep experience in data cleaning, integration, and harmonization. Our data organization services include:

  • Cleaning and Curating Data
  • Creating Custom Ontologies and Controlled Vocabularies
  • Creating Custom Data Hierarchies

We support pharmaceutical, biotech, and diagnostics companies to organize data for research applications.

02/ Curation

Generation of Multi -omics Datasets for Target Discovery

We leverage our expertise in omics technologies to untangle crucial insights in the fields of oncology, immunology, and drug discovery. We generate single-cell, spatial transcriptomics, and genomics data from clinical samples in our India-based CAP lab. Our accomplishments in this realm include certification as a service provider for 10X Genomics Visium Spatial Transcriptomics workflow.

02/ Curation

Building Custom Bioinformatics Pipelines

We develop custom pipelines for use in drug discovery and oncology research. Our bioinformatics expertise holds us in good stead when it comes to tackling cutting-edge problems in the field. Our solutions span across:

  • Cell-type deconvolution for single-cell spatial transcriptomics data
  • Analysis of fragmentomics data
  • Early cancer detection and development
  • Refactoring
  • Optimizing
  • Benchmarking algorithms for secondary analysis toolkits
03/ Getting curious about our RWD solutions

Frequently Asked Questions

Strand’s data harmonization process ensures that large datasets are handled in a timely and accurate manner, significantly improving efficiency. Our hierarchical structure organizes data from diseases to core data, making it easily navigable. We successfully harmonized over 500 datasets and implemented this structure for a top 20 pharmaceutical company in the US. This included a variety of data types, such as metadata files, raw data and processed data of various types, and post-analysis files. See A Case Study on Data Harmonization for a Big Pharmaceutical Company for more information.
Absolutely. Strand’s multidisciplinary team of curators, bioinformaticians, and data engineers work together to harmonize heterogeneous data. Our process includes standardizing terminologies, building NLP-powered dictionaries, and creating custom ontologies to resolve inconsistencies. See A Case Study on Data Harmonization for a Big Pharmaceutical Company for more information.
Strand’s expert curators, with deep domain knowledge and extensive experience across multiple modalities, meticulously generate gold-standard datasets. This resolves ambiguities and inconsistencies in biomedical terminology, essential for the accurate extraction of relationships between entities. See A Case Study on Ground Truth Dataset Curation for a Major Diagnostics Company for more information.
Our client, a diagnostics company, required an NLP algorithm for extracting molecular or genetic data from somatic cancer publications. Strand’s team of curators and reviewers annotated entities and relationships pertaining to genes, diseases, biomarkers, and more for over 1,000 excerpts using brat, an open-source tool. As a result, we delivered a meticulously annotated ground-truth dataset for benchmarking the client’s NLP algorithm. See A Case Study on Ground Truth Dataset Curation for a Major Diagnostics Company for more information.
Strand’s researchers have evaluated various state-of-the-art and novel methods and developed an end-to-end bioinformatics pipeline that is optimized for speed and robustness. The main processes in the pipelines such as clustering analysis and cell type annotation were optimized through a systematic evaluation of publicly available tools and databases. See Spatial Transcriptomics Data Analysis Pipeline for Research and Diagnostics for more information.
03/ CONNECT

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