Health and pharma companies can exploit their unstructured information

There are new kinds of data that are specific to the healthcare and pharmaceutical industries (such as electronic health records) as well as data science tools that allow us to extract valuable knowledge from that data.

 

With MeaningCloud, it is possible to identify the costs of medical treatments, their efficiency (cost, benefits, and risks), references to drugs, side effects, or long-term results. That is why our text analytics solution for the healthcare and pharma domains has so much potential.


Most promising areas of text analytics in the pharma sector

Austerity measures and related drug price cuts have put unprecedented pressure on the pharmaceutical industry. Manufacturers are asked to provide information related not only to safety, proper use, and effectiveness of their products, but also to their clinical and economic value. The pharma industry is among the ones that most can benefit from the application of technologies for the intelligent analysis of free text

Our company maintains a constant development line focused on the pharmaceutical and life sciences industries: around 80% of our revenue comes from that sector. There are hundreds of thousands of domain-specific semantic resources integrated into the system, each of them intended to detect a different type of named entity. They include MedDRA, UMLS, CIMA, ATC and IDC.

Voice of the Patient

For pharmaceutical companies, it is vital to understand the feedback that their current and potential customers express through all types of channels and contact points. The Voice of the Patient enables to extend preexisting information with data coming from unstructured content: comments on health forums, social networks, surveys, records from call centers, etc.

Analysis of Electronic Health Records

New data technology has introduced electronic health records and customized information repositories. Our company is able to offer analytical tools to evaluate the cost of medical treatments, their efficiency (cost, benefits, and risks), references to drugs, side effects, or long term results of procedures.

Data integration and analysis

Healthcare and pharma companies can gather and leverage the most valuable business information that is scattered on a ton of websites with different structures. The ability to crawl all those data and store them under a common data storage is crucial to approach any data analytics process. The combination of crawling and text analysis makes it easier to gather only relevant data.

Scientific research

Each year, 1 million new citations are added to PubMed. Leveraging artificial intelligence, we explore large data stores to discover valuable information and knowledge resources. In scientific research, text analytics is used to mine large volumes of articles and other documents, identify relationships, and facilitate information retrieval.


Recommended products for the pharmaceutical industry

Among the text analytics technologies beneficial for the pharma sector, we can highlight:

Topics Extraction API

Complete semantic annotation of contents including entities (persons, organizations, concepts, themes…) , key concepts and relevant data (amounts, date and email).

Text Classification API

Build a classifier of your own with this powerful hibrid classification engine to match your workflow and route claims depending on theme, products or channel.

Corporate Reputation API

Analyze corporate reputation of your brand. Compare it with your main competitors. Detect in real time any menace for your corporate reputation from the analysis of social media content.

These are just some of the MeaningCloud solutions recommended for healthcare and pharma companies, but there are more. Be sure to have a look our product catalog.


Advantages of MeaningCloud for the pharma industry

MeaningCloud's solutions aimed at the pharma industry gather our expertise in projects for this industry and provide services for tagging, enriching and proofreading contents. These are some of their features:

Discover relations hidden in text

Extract relations, e.g. "adherence" or "side-effects".

Classify in categories

Classify text according to custom taxonomies or classification schemes (e.g. patient experience: pain, discomfort, difficult to apply, etc.).

Identify keywords

Identify relevant concepts (e.g. negligence, drug, medical expenses, emergency room, etc.).

Use your own dictionaries

Names of companies, hospitals, trademarks, products, services, etc. can be added to system dictionaries for customization purposes.

Extract key data

Identification of money amounts, dates, time expressions, addresses, URLs and e-mail addresses.

Integrable with your ERPS, CRM, or CMS

Easy to integrate with your Customer Relationship Management solution or Content Management Systems.



Our clients

Pfizer
Novo Nordisk

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