Healthcare and Life Sciences

Pharma /Healthcare and Life Sciences

Pharma and healthcare companies are saddled with the burden of increasing competition, regulatory issues and speed of innovation. Competitive pressure forces pharma companies to implement innovative technological solutions to enable faster speed to market. The new emerging concept of Real World Data is catching up very fast. Enterprises are looking towards collaboration opportunities with HealthTech firms to accelerate growth and expand on business models. Large healthcare and pharmaceutical companies have been announcing their focus on data.

why healthcare data is difficult


Image Source: HealthCatalyst

Challenges & Solutions


Regulatory Compliance

Regulatory compliance has emerged as a significant concern for pharma companies, as regulatory fees and penalties have increased dramatically relative to earnings. Issues related to regulatory compliance include:

Multiple Jurisdictions /Regulations

Cross border legislature and regulations maintaining strict compliance places significant strains on resources

Heavy Penalties & Fees

Faced with severe consequences for non-compliance, keeping abreast of regulatory changes and implementing the controls necessary to satisfy requirements have resulted in increased cost and risk. Overcoming regulatory compliance challenges requires fostering a culture of compliance within the organization while also implementing formal compliance processes and systems

Cost of Compliance

Additionally, costs associated with compliance management are also a major factor that is forcing pharma companies to change the way they do business. This combination of factors has led many institutions to create seek efficient data technology and reporting

Data Intensive

Regulations and compliance today are heavily dependent on the ability to correlate data from disparate data sources


Converging data architectures

Inefficient multiple legacy technologies are creating problems that pharma companies have to deal with. However, the use of AI, Big Data is helping companies efficiently use data and innovating.


Implementing value-based reimbursement

Value-based reimbursement ties payments to quality rather than quantity.

  1. End to End Processing: Lack of end to end solutions for value-based payment
  2. Value Based Care Solutions: Delivering value-based care requires different infrastructure, work flow, and information than what has been in place historically, all of which require investment.


Organizations using inefficient, clunky and expensive technologies will not be able to keep up with this demand for efficient data. Technologies like cloud computing, artificial intelligence (AI), machine learning (MI) and Big Data all offer significant advantages for institutions looking to reduce costs and increasing profits. They enable firms previously burdened with disparate legacy systems to make thing simple, smart and efficient.


Real World Date (RWD)

  1. Real World Data (RWD) is fundamental to capturing the benefit and risk after a product has received regulatory approval
  2. Issues in data collection from sources outside of traditional clinical trials need to be addressed

Research Publication data extraction

Efficient Data Extraction

Data monitoring committees require quick data extraction from voluminous reports. Due to diversity of reports, data is spread across numerous sources

Pattern detection

AI enabled programs can assist in detecting patterns in reports

Format Conversion

Extraction of data from PDF and populating data in specified tables


The ability to use AI, Big Data to provide end to end process for conversion of reports could be made very efficient


Reach out to us to know how HEXANIKA can address these issues

Business Outcomes


Global Lifesciences Company

Adverse Event Detection Using Predictive Analytics

40% Savings

Time & Cost Due To Process Automation


US Health Insurance Org

Insurance Billing & Reporting

50% Savings

Reduced Customization Cost & Time For Report Rendering