Lend Rx is at the forefront of providing a diverse array of datasets within the healthcare sector, focusing on Therapeutics and Companies. Our global coverage spans over 15,000 Therapeutics, ranging from Research and Development (R&D) to Generic stages, associated with more than 5,000 Companies, which includes 1,500 listed companies and their respective tickers.
Our approach is comprehensive, involving the collection, connection, analysis, and aggregation of data from thousands of sources. Lend-Rx seamlessly structures a range of datasets, from raw data up to investment signals.
Leveraging our proprietary Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies, we analyze unstructured text content to deliver disambiguated information and structure data, including topics, outcomes, and sentiment. Driven by rules and machine learning algorithms, Lend-Rx generates additional Key Performance Indicators (KPIs).
A quant friendly format focusing on :
- Detailed mappings starting from Therapeutics to Companies and Tickers, but also additional mapping Therapeutics to stages of development and diseases…
- Commitment to accuracy and timelines with historical points in time data, timestamping and unbiased dates
- Data releases up to daily intervals and a remarkably short lag period, as brief as 2 hours
- Delivery under S3 or Snowflake
RxClinicalTrials drives our clients through the clinical trials of the global therapeutic landscape. Combined with our unique daily updated point-in-time Mapping Therapeutics to companies, the client can monitor companies’ past and ongoing trials on a daily basis mapped to products, trial results released and trial success or failure.
• Multiple sources of information. For each Trial, Lend-Rx collects and interoperates several public sources of information such as medical registries, Press Releases, Agency disclosures…
• Clean Therapeutic, disease and company names. Lend-Rx Tech Natural Language Processing platform, combines semantic analysis, taxonomy and ontology to disambiguate therapeutics and diseases synonyms.
• Trial results. Official trial results releases collected from Press Releases, Medical Conference presentation or MedicalJournals. Trial Results outcomes are tagged with the success or failure. Trial discontinuation extracted from Medical registries are tagged with reason for discontinuation.
• Changes in trials. Lend Rx compiles changes in information from medical registries, to deliver structure data like delays and a clear explanation for early termination.
• Unbiased timing of information. Lend Rx time stamp every source of information from data collection to delivery. Dates within dataset are at date of availability and collection and not date extracted from the document.
• Mapping of Trials to therapeutics and companies. Leverage unique Therapeutics to Company mapping with historical point in time mapping and timestamping data since 2016.
The dataset provides dynamic data at the Trial level: for a given timestamp of validity (RELEASE_DATE), we deliver one delta file on a daily frequency (cf. RELEASE_DATE). Delivery is through S3, and Data Dictionary is available on request.
The RxClinicalTrials dataset can be bundled with RxMappy to add Therapeutics’ KPIs and metadata into Machine Learning for likelihood of Clinical Trial Success or likelihood of approval calculation purposes.
Rx-Mappy drives our client through the development journey from the preclinical to the generic stage of the global therapeutic landscape. Combined with our unique daily updated point-in-time Mapping Therapeutics to companies, the client can monitor companies’ pipelines and portfolios on a daily basis and look forward with product-based catalysts calendar.
• Multiple sources of information. For each Therapeutics, Lend-Rx interoperates several public sources of information from medical registries, Press Releases, Agency disclosures…
• Clean Therapeutic, disease and company names. Lend-Rx Tech Natural Language Processing platform, combines semantic analysis, taxonomy and ontology to disambiguate therapeutics and diseases synonyms.
• Therapeutics Classification covering all Therapeutics including products in R&D stage.
• Unbiased timing of information. Lend Rx assign a time stamp to each piece of information from data collection to delivery. Dates within the dataset reflect the date of availability and collection, not the date extracted from the document, which often precede the value date.
• Therapeutics KPIs such as First in Class Therapeutics, Therapeutic Target validated… for ML features building
• Curated Therapeutics Metadata, benefit from Lend-Rx Tech's expertise in healthcare to enrich Therapeutics Key Metadata such as biological targets, drug type, mode of action.
• Mapping therapeutics to companies. Leverage unique Therapeutics to Companies mapping with historical point in time mapping and timestamping data since 2016.
The dataset provides dynamic data at the drug level: for a given timestamp of validity (RELEASE_DATE), we deliver two files, Rx_mapping and Rx_Metadata, and for each drug (DRUG_ID). Datasets are released at a daily frequency (cf. RELEASE_DATE). Delivery is through S3, and Data Dictionary is available on request.
A full historical dataset is available for data analysis and backtesting with data trial agreement.
The Lend_RxListener dataset encompasses social media data worldwide, tracking Therapeutics from their Research and Development (R&D) phase to their generic date. This dataset employs a historical point in time mapping of Therapeutics utilizing a bottom-up approach to aggregate social media topics and sentiment related to Tickers associated with Therapeutics.
Within this dataset, expert knowledge and the public perception of therapeutics, as shared on social networks, are captured. The data is generated by our proprietary biomedical natural language algorithms, which are integral to the Doltracker platform. For more details on audience intelligence and listening with Doltracker, please refer to our website.
The dataset provides dynamic data at the drug level: for a given timestamp of validity (RELEASE_DATE), we deliver two files covering mapping of Therapeutics to company and daily topics and sentiment for each Therapeutic. Datasets are released at a daily frequency delivered through S3.
Lend_RxNewsCatalysts dataset covers past and upcoming events about therapeutics mapped to 5K+ biotech and pharma companies including 1.5K Tickers. Lend-Rx leverage on its AI and NLP platform to interoperate and analyze content of Press Release and Medical Registries information and aggregate information at the Ticker and company level.
Lend_RxNewsCatalysts is a processed dataset that aggregates for each Ticker:
• Press release figures categorized based on outcome analysis (positive or negative) across multiple retrospective time intervals
• Anticipated count of Events segregated by clinical stage and temporal intervals
• Anticipated count of KEY Events categorized by clinical stage and temporal intervals
The dataset provides dynamic data at the Ticker level: for a given timestamp of validity (RELEASE_DATE), we deliver a full refresh file on a weekly frequency through S3.
RxDominews is a dataset covering the ripple effects of therapeutics Events from public and private companies to related Tickers employing a causality link approach. The Events are categorized based on type including outcomes from Clinical Trials and registration milestones. The Data encompasses circa 1500 biotech and pharma tickers.
Dominews offers:
• The nature of Therapeutic Events: Clinical Trial Phase 3 results, Registration milestones.
• The Ticker or the name of the company that owns the Therapeutic.
• Contaminated Tickers of companies owning similar therapeutic with conditions such as targeted diseases, development phase…
• A minimal lag, as the dataset covers events up to current day noon UTC.
Lend Rx employs its proprietary Biomedical Natural Processing to scrutinize Press Releases released by companies, providing insights into the type and outcome (positive or negative) of the events.
Lend Rx computes the ripple effect using its exclusive knowledge base and therapeutic classification, encompassing both approved and research and development (R&D) products.
Data usage
Lend_RxDominews is a dataset oriented towards trading given the unpredictable nature of idiosyncratic events, such as clinical trial results or registration decisions, in terms of timing, frequency, and binary events nature. Overall the datasets contains hundreds of events over its historical period.
Data delivery
The dataset provides dynamic data at the ticker level: for a given timestamp of validity (RELEASE_DATE), we deliver data covering Events from the previous day noon UTC to current day (RELEASE_DATE) a file covering all tickers contaminated by a therapeutics Events. Datasets are released at a daily frequency delivered through S3.
• Timestamping: Apply multiple time stamps from collection time to delivery.
• Point in Time data: No survival biases, tickers from takeover target and delisted companies included.
• Tickerization: and additional company’s identifier.