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DOCstore Semantic Search Engine

Search, analysis and storage for semantically indexed content

Disclaimer: DOCstore was discontinued as of March 2021 and replaced by our next-generation scientific search and analytics platform, SciBite Search.

 

How often have you searched for something and had to iterate through multiple different terms and synonyms to get to the right answer?

DOCstore enables researchers to harness the power of semantic analysis search to rapidly and comprehensively scan multiple biomedical sources.

It represents a paradigm shift in literature searching and supports a wide range of use cases, from identifying new drug discovery opportunities to monitoring the competitive landscape for a disease of interest.

Simple to setup yet powerful enough to handle millions of records, DOCstore offers scientifically aware search and analysis capabilities at the click of a button.

Easy to deploy and intuitive to learn, DOCstore can be installed in under 20 minutes and be run from a mobile device, standard laptop or through a designated server providing flexible access to its powerful capabilities.

Get in touch with the team to learn more or download the DOCstore datasheet.

Download datasheet

Key product highlights

  • Comprehensive icon / pictograph

    Comprehensive

    Rapidly find all of the most relevant information, regardless of what synonym you use as the search term

  • Connections icon / pictograph

    Identify Connections

    Instantly see co-occurring entities at the document and sentence level, such as connected genes, diseases and drugs

  • Informed icon / pictograph

    Keep Informed

    Set-up automatic email alerts to stay up-to-date

  • Powerful icon / pictograph

    Powerful Analytics

    Built-in analytics make it easy to consume large volumes of data and visualise trending authors and topics over time

Want to learn more about DOCstore?

Get in touch with us to find out how we can transform your data

Contact us

Use cases

Comprehensive competitive intelligence monitoring in real time
[Use case]

Most pharmaceutical companies struggle to maintain an up-to-date awareness of the latest biomedical research relevant to their own therapeutic programmes. Competitor intelligence monitoring typically involves a manual approach involving the time consuming, piecemeal review of a small range of data sources.

However, the exponentially growing amount of literature and increasingly diverse range of sources make it almost impossible to maintain a comprehensive and up-to-date understanding. The result is that the legacy approach to literature scanning is no longer practical.

SciBite’s resource-effective solution uses semantic analytics to reduce both the time and uncertainty involved in evaluating the vast body of research and news to track trends, gain early insight into potentially ground-breaking scientific advances.

Read the full use case

Enabling a Modern, Efficient Approach to Pharmacovigilance
[Use Case]

Regulatory bodies expect pharmaceutical companies to maintain an up-to-date awareness of the safety implications of not only their own drugs but also those from the same drug class and with the same target that are marketed by competitors. Comprehensive, systematic monitoring is required in order to detect, validate and act upon new adverse events as early as possible.

This places significant demands on Pharmacovigilance teams, who are challenged to maintain safety and compliance amid increasingly stringent, globally diverse regulations. The legacy approach, involving manually scanning biomedical sources, is prohibitively time consuming, has a high risk of missing safety signals and is no longer a viable option.

Read the full use case

Semantic Analytics: A Systematic, Data-Driven Approach to Drug Repositioning
[Whitepaper]

A growing number of pharmaceutical companies are turning to Drug Repositioning as a cost-effective alternative to de novo drug development. Their goal is to discover new uses for drugs to treat clinical indications other than those for which they were originally intended and to accelerate the provision of new, safe treatments to underserved patient communities.

However, traditional approaches to Drug Repositioning rely on structured data sources, sometimes supplemented by searches of the literature. Due to the manual, time consuming nature of such searches, they are limited in scope and miss potentially important information.

Semantic analytics facilitates the rapid identification of drug-target-indication relationships from a wide range of heterogeneous and cross-disciplinary sources. The SciBite Platform makes semantic analytics accessible to pharmaceutical companies, expedites the identification and prioritisation of all possible repositioning options associated with one or more drugs of interest and ensures decisions are based on all the available evidence.

Read the full use case

Semantic Analytics: Integrated approach for pharmacovigilance teams to achieve awareness
[Whitepaper]

Regulatory bodies expect pharmaceutical companies to maintain an up-to-date awareness of the safety implications of not only their own drugs but also those from the same drug class and with the same target that are marketed by competitors. Comprehensive, systematic monitoring is required in order to detect, validate and act upon new adverse events as early as possible.

This places significant demands on Pharmacovigilance teams, who are challenged to maintain safety and compliance amid increasingly stringent, globally diverse regulations. The legacy approach, involving manually scanning biomedical sources, is prohibitively time consuming, has a high risk of missing safety signals and is no longer a viable option.

SciBite provides a resource-effective solution to the challenges faced by Pharmacovigilance teams by unlocking the potential of unstructured biomedical content. With semantic analytics, pharmaceutical companies can monitor a wide range of heterogeneous and cross-disciplinary sources and reach timely, well-informed decisions, resulting in safer treatments for patients.

Read the full use case

Semantic Enrichment and The Information Manager
[Whitepaper]

It is more resource intensive to bring a drug to market than ever before: Pharmaceutical companies spend an average of at least 10 years and $2.6 billion on each successful outcome, yet fewer than 1% of potential drugs are ever made available for sale. At the same time, the growth in volume of published research is accelerating: More scientific research published between 2010 and 2014 was indexed in MEDLINE than all research published before 1970.

Drug development professionals know well the daily struggle of staying current with a multiplying volume of multitudinous types of information: peer-reviewed scientific research, patent flings, clinical trials data, news and competitive briefs, conference abstracts and posters, and more.

This paper explores these challenges, and how semantic enrichment can provide a foundation to open new opportunities to quickly extract insights from information.

Read the full use case

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