For Pharma and Bio-Pharma, Data Is a Potential Blockbuster - Stefanini

For Pharma And Bio-Pharma, Data Is A Potential Blockbuster

Leveraging data to produce crucial insights

By Nagesh Jadhav, Director, Digital Transformation and Innovation HCLS

“Data is the new oil” is the saying recently made popular in the industry, for Pharma and Bio-Pharma data is the new potential blockbuster. With rapid advancements in scientific and disruptive technologies, pharma and biopharma companies have generated and are experiencing a deluge of information and data across the enterprise. The data is expected to grow exponentially and traditional data management and analytics techniques will not be able to handle and process this voluminous data.

The growing and complex data from Labs, Omics, R&D, Clinical Trials, Regulatory, Sensors, Smart Pills and Devices, Medical Safety and Health records, Manufacturing and Supply Chain, Sales and Marketing, Social media demands new and transformative techniques, tools and infrastructure to integrate huge structured and unstructured data effectively, cleanse, manage and visualize data for insights and decisions. The major challenge is to integrate data from heterogeneous systems and across functions, transform it into easily accessible, compliant, sharable, reportable form and actionable insights for informed decisions.

Gaining Insight from Big Data and Analytics

This article gives the benefits and value, life sciences organization can gain from big data and analytics. For Pharmaceuticals and Bio-Pharmaceuticals the insightful and informed decisions derived from data across functions would enable expedite new discoveries, optimize trials, expedite regulatory approvals, improve compliance, bring operational efficiencies, increase patient outcomes, define appropriate pricing and brand positioning, bring personalized and precision medicine to the market. The composite value of all these could amount to a business value of a potential blockbuster for mid- to large-Pharmaceutical and Bio-pharmaceutical organizations.

1)     R&D

One of the biggest challenge life sciences organizations facing are the dwindling drug pipeline and patent expires. To overcome these challenges life sciences organizations, need to expedite the R&D processes. The R&D organizations generate complex and humongous data from the sequencing and HTS equipment. The data generated is growing exponentially and cannot be effectively managed and handled with conventional data management approach. Leveraging Big data and analytics technologies to store and analyze the large-scale genomic and drug discovery data could expedite R&D and help focus the fast-growing drug pipeline.

Expedite R&D for innovation and new therapies

–        In silico drug screening for lead identification

–        Target and biomarker identification, disease characterization and prevention.

–        Toxicity and efficacy prediction

–        Genotype to Phenotype diagnostics

–        With predictive analytics create more efficient and targeted drug pipeline

–        Study disease progression with large datasets of genomic, proteomic, celomic, phenotype and clinical studies

–        LIMS, ELN and Lab equipment data to bring more operational efficiencies and streamlining processes

2)     Clinical Trials and Operations

Clinical Trials generate large-scale datasets, these could be used to increase operational efficiencies in clinical trial operations. Big data and analytics could help effectively store and analyze data to optimize future trials with predictive analytics and simulation techniques. Analytics could also be done to identify sites and select investigators and patients. The historic clinical supply data could be effectively used to manage and streamline clinical and product supplies, identify, foresee and avoid delivery issues.

Optimize Trials and Clinical Development Operations

–        With statistical tools and modeling, enable Trial simulation and optimization

–        Predictive modeling and insights could help Investigator, site selection and patient identification recruitment

–        Asset Prioritization and streamlining trial supplies

3)     Regulatory Compliance and Product Safety

The Life sciences industry is one of the most regulated and compliance-intensive industries. The key to compliance is easy availability and accessibility of information required by regulatory agencies. Big data and analytics could help efficient store large historical data and grant easy access to required information in reportable formats. Big data enables efficient integration and storage of primary and secondary data be it structured from EMRs and EHRs, claims data, semi-structured or unstructured data from social media. Analytics of data and data sets helps gain insights of safety efficacy and get safety signals to avoid adverse and serious adverse events.

Faster regulatory approvals and increased compliance

–        Improved data quality and faster, easy access to information for submissions

–        Insights and information of site performance and site quality to reduce compliance risks

Increased drug effectiveness and safety

–        Determine treatment effectiveness through information from EMR’s online communities and social media to gain insights

–        Get early safety signals from various sources to avoid adverse and serious adverse events

4)     Manufacturing and Supply Chain

The Manufacturing and supply chain industry are not untouched by digital disruption. The drug manufacturing and supply chain systems, process historian systems, building management equipment, maintenance systems and sensors on factory floors, and the automated Internet of Things (IoT) are spitting enormous data every second. The data generated can be used to gain insights and signal to track batch process raw material and supplies, check temperatures and control, predict equipment failures, streamline and control processes, get critical alerts and triggers to avoid and mitigate risks. Data and insights derived from supply chains could be used to forecast demand and match supply.

Improved manufacturing and supply chain efficiencies

–        Get data from factory floor sensors, manufacturing systems for actionable insights to control processes, increase efficiencies and manufacturing quality

–        Get critical alert signals or triggers on temperatures, equipment failures

–        Get data from supply chain sensors and insights for decisions to increase operational efficiencies.

5)     Health and Wellness

With the proliferation of smart healthcare devices, smart pills and the growing use of social media by patients, a large amount of data is available to track and monitor patients’ health and wellness. Miniature biosensors could be used to monitor and track patients’ adherence. Smart pills enable tracking of safety efficacy and drug interactions in the body as it progresses through the system. The aggregate data generated could be used to track and monitor population health and wellness index. The enormous amount of real-world data generated from smart sensors, bottles, devices pills and social media could be used to increase drug efficacy and safety, prevent adverse events, increase adherence and bring new and economic models of provisioning medicines and healthcare services. With an increase in genomic diagnosis services and the availability of data from genomic diagnosis and across the drug lifecycle could help bring personalized care and precision medicine.

Increased patient adherence and improved outcomes

–        Monitor adherence through devices, wearables and prescriptions

–        Smart devices and smart pills to track and monitor health outcomes, access data from social media

Information for Real World Evidence (RWE)

–        Gain access to genomic, trail, safety data, EMR’s and social media data for real world insights and decisions for value-based pricing and improved patient outcomes

Provide Personalized and precision medicine

–        Utilize Genomic diagnosis, EHR, trials, treatment, Safety, social media, behavior and demographic data to provide personalized services and precision medicine.

6)     Commercial

Pharma and Biopharma companies spend approximately 20 to 30% of their revenues for sales, general and administration. With massive data available from current field sales, historical sales and marketing, disease demographics, marketing campaigns, and data from social media. Big data, advanced and predictive analytics could be used to model and optimize sales force, run targeted, focused personalized marketing campaigns, help effective brand launch, cross and upsell products. The data available across the drug life from bench-to-bedside could help give a complete 360 degree view of patients and doctors to enhance sales and provide better and cost-effective services. The large amount of data available from the 3 P’s (Patient, Provider and Payer) could be used to derive right and value-based pricing with insights from analytics. Big data and Analytics could increase efficiencies and effectiveness of sales and marketing function to provide better effective and personalized care and services.

Increase Sales and Marketing effectiveness

–        Get consumer trends and insights for effective and targeted sales and marketing strategies

–        Perform predictive modeling and advanced analytics for brand positioning and product launch

–        Get insights and information from multiple sources for 360 degree view of doctors and patients

–        Right and value-based pricing with insights from payer, provider and patient data


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