When the Covid-19 pandemic struck the world, the importance of digital technologies in every aspect of life became incontrovertible. Every industry and individual had to shift their communications to digital platforms. Supply chain disruption forced global industries to adopt technologies to improve visibility, collaboration, and agility.
In the life sciences and healthcare industries, the pandemic forced companies and countries to accelerate implementation of digital technologies – from telemedicine, to virtual clinical trials, to the imperative to share more data faster and in a harmonised way for innovation and to support public health. According to a GlobalData survey, 35% of pharmaceutical professionals say the pandemic sped up the digital transformation by more than five years.
To better understand how the achievements to date have been possible – and how far we still have to travel – it’s important to assess how we got to this point in digitalisation. The origins of the journey towards digital transformation can be traced back more than 50 years and across multiple industries. From sharable and structured databases, supported by industry standardisation to the emergence of technology solutions such as EDMS and ECM to support large sets of documents and data in electronic format, the world of information storage, sharing, and traceability had been revolutionised in a short period of time.

However, what we now refer to as the digital transformation began in earnest with the ability to exchange data through portals and networks and later with the introduction of blockchain technologies to secure these exchanges. More recently, digitalisation has made huge leaps forward with sensors, such as wearables and smart phones, and the ability to gain smart insights from data through natural language processing, semantic networks, machine learning, and other artificial intelligence technologies.
The next challenge in the shift to a digital-first approach has been navigating this rich and complex landscape in a way that allows users to establish the rationale for searching and analysing data, for example, searching for data linked to a specific piece of technology or using keywords to navigate across multiple data sources to better understand a concept. Today, there is an array of tools that facilitate navigation across multiple digital sources either using a predefined reference model for interoperability (Identification of Medicinal Product in the pharmaceutical industry) or leveraging AI tools, such as web browsing or automated learning and smart connectors to support navigation.
The final element enabling the digital transformation is the technologies enabling agile and efficient interoperability, such as cloud-based infrastructure and enterprise-wide IT architecture overhauls.

Digital momentum

With the four levers enabling digital transformation well advanced, businesses can improve and streamline processes and activities across the enterprise to enhance innovation and drive better insights. These include:
• Process optimisation – robotic process automation allows companies to carry out repetitive tasks, for example the management of clinical trial data or streamlining compliance and reporting. According to a 2020 Bain & Company survey, 81% of healthcare companies are seeking to accelerate automation initiatives.
• Trend assessment, data analytics and simulation — for the assessment and analysis of data and patterns within the data to extract knowledge (for example, risk signals), predict (for example, using in-silico models in clinical trials) and to simulate a situation through modelling or virtual reality.
• Exploit “Big Data” – to improve knowledge, for example about a disease or therapeutic target; to identify trends that could affect a product or activity; identify new opportunities.
• Business process re-engineering – integrating data centricity and data quality to better manage the massive amount of data that makes it hard to effectively achieve data analytics, big data extraction for improved knowledge, and trend identification.
• Product lifecycle management – to improve traceability and real-time oversight of the product from research to clinical trials to manufacturing to post-market evaluation to product withdrawal.
• Data and process coordination, control, and management – integration of digital tools to manage and exploit data for activities such as forecast planning, execution planning, workflows, track and trace and warning systems, and KPI dashboards.
• Digital insights for total cost of ownership — leveraging economic data, operational and experiential data to evaluate, improve, and even rethink the business model.
To take advantage of the digital capabilities to improve quality and enhance business development, organisations will need to adopt a multi-faceted approach to their digital transformation.

Digital Momentum: Transformation Across the Life Sciences

Digital health is disrupting how life sciences companies operate, how they deliver products and services, how they manage processes, and how they collaborate and build relationships with patients, healthcare professionals, partners, and regulators.
In the regulatory realm, digitalisation has the potential to transform many activities – from speeding up and improving quality for many repetitive data entry activities, to enabling better product lifecycle management, to enhancing regulatory intelligence. The U.S. Food and Drug Administration (FDA) has taken a lead on digitalisation through various strategies designed to improve review and monitoring activities. Most recently, the agency’s Data Modernization Plan (DMAP) aims to deliver greater value through projects that will inform modernisation.

Limiting the document complexity with RPA

Robotic process automation (RPA) has been defined as a technology that “mimics the actions of a human performing simple rule-based processes.” Use of RPA is accelerating across industries, with more than 90 percent of respondents to an Economist Intelligence Business Unit survey saying their organisations are using RPA.
Since marketing authorisation applications and health technology assessment (HTA) dossiers as well as many other regulatory documents contain data that is stored in digital sources, such as regulatory information management (RIM) solutions, they are good candidates for automated data filling.
RPA assumes documents have a predefined structure, which is not always the case. However, creating and storing templates (per company or even country requirement) assists with the process and even without RPA helps to improve efficiency and quality in document preparation. Once a document is created, digital tools can be leveraged to carry out automated quality checks of the data. Furthermore, if the document structure is standardised, it is easier to extract data from it.

Product Information

Digital information across the product lifecycle is gathering momentum as evidenced by EMA’s principles for use of electronic product information for medicines across the EU.
As regulatory authorities demand full data transparency, there is a growing trend to share information using digital formats. To facilitate this exchange of information between different systems, models such as IDMP (Identification of Medicinal Product) and data management services such as SPOR (substances, products, organisations and referentials) and RIM are being used, ensuring a single source of truth for data.
Internally, companies are adopting digital processes to produce and track the Core Company Data Sheet (CCDS), ensuring traceability and consistency of data across the life cycle of a product. There are collaborative initiatives between industry and the regulators, such as the Accumulus Synergy, aimed at improving the exchange of information and data to help bring medicines to market faster.
Ultimately, data will be shared across countries to cross-check differences and commonalities, streamlining cross-checks of variations and country-specific requirements. Together, all these digital transformations will fundamentally change the responsibilities and workload of regulatory affairs.

Risk management

Life sciences companies must submit a risk management plan to regulators when applying for marketing authorisation, demonstrating the product’s safety profile, plans to prevent or minimise risk to patients and plans to measure those strategies, and plans for ongoing studies. Risk management plans apply to all aspects of product development, with guidance from national authorities as well as ICH recommendations.
The digital transformation will play an integral role in supporting and enhancing risk management activities by making it easier to collect and assess a wide range of data to identify and analyse risk and to document and trace decisions.

Benefit-Risk evaluations

During the past two decades there has been a shift in the approach to evaluating the benefit–risk profiles of medicinal products using a more structured and objective process. A decade ago, EMA brought out guidance that makes the agency’s assessment of the benefits and risks of a medicine more consistent, transparent, and easier to audit. Similarly, FDA developed a structured, qualitative benefit-risk framework.
FDA is also making use of real-world evidence (RWE) to monitor post-market safety and to support regulatory decision-making.
These approaches are deeply connected to the digital transformation since they lay out the methodology for identifying the needed data and models for evaluating the benefit-risk balance. As an example, EMA’s guidance includes how data captured from wearables used in clinical studies support the benefit-risk assessment, according to a commentary piece in Nature authored by representatives from industry and EMA.
“The rational adoption of adequately qualified digital technologies will support novel data collection methods while ensuring their regulatory validity,” the authors note.

Safety and pharmacovigilance: case reports

The push to standardise case report forms as well as safety reports (DSURs, PSURs and RMPs) makes safety and PV the perfect candidate for RPA. In addition, literature searching lends itself to automation supported by AI tools to speed up processes and enable organisations to expand and deepen their searches.
According to a Deloitte survey report, many pharmaceutical companies have been assessing how to leverage digital solutions such as automation, cognitive technologies, and advanced analytics to achieve an advanced learning system to improve safety across the life cycle of a product.
Reducing the cost of case processing through cognitive automation is a primary goal for 90% or organisations, while improving signalling for better benefit-risk management is a priority for more than 90%, the report finds.
The pressure to protect patients and anticipate risks, meanwhile, has led to AI-enabled signal detection to analyse databases as well as social networks. As the focus on social responsibility combined with business risk anticipation intensifies, a digital framework supported by AI and big data will become mandatory for a proactive safety value chain.

Regulatory operations and CMC

Most regulatory operations activities – publishing, labelling, packaging, and exchanges with the authorities – will benefit from full automation. On the CMC side, meanwhile, there is a huge focus on automating document filling and quality checks.
To harmonise processes, it will make sense for organisations to centralise CMC data sources in a cloud-based system. At a more strategic level, the use of data analytics and risk management approaches, for example, Quality by Design, will help to streamline audits and potentially even reduce the risk of inspections.

Compliance, manufacturing, and supply chain

Digital quality documentation and production records will help to harmonise processes, reduce data entry errors, speed up good manufacturing process reviews and support the overall supply chain.
In recent years, GMP data integrity has become a bigger priority for regulators, with both EMA and FDA issuing guidance on the issue. The FDA has issued many warning letters for data integrity violations. Digitising these records can assist with compliance with regulations and traceability of records.

Market access

The collaboration between EMA and EUnetHTA, which was put in place to create synergies between the regulatory review process and health technology assessment evaluations, underscores the value and importance of digitising data sources related to the product.
By making use of digital intelligence for insights about other therapeutics in the same class and competitors, companies gain a complete picture of the profile of the drug and category, which can not only support the regulatory strategy but also provide evidence to support market access discussions.

Patient-centricity and digital devices

Patient-centricity puts patients at the centre of all aspects of product design and development, from inclusion in therapeutic development processes, to clinical trial design, to risk mitigation plans, to a wide range of EMA activities.
Digital devices will help to further elevate patient-centricity. In clinical trials, for example, not only will researchers be able to closely monitor the patient’s experience, but digital devices will reduce the number of hospital or site visits patients need to make.
Crucially for patients, the digital transformation will support precision medicine by making it possible for companies and clinicians to adapt treatment to a patient’s changing health status. For example, in its report, “Digitalization in Life Sciences: Integrating the patient pathway into the technology ecosystem”, KPMG notes that digitalisation will enable dosages to be customised per patient, depending on disease progress and patient characteristics and even the potential for smart drug production hubs for customised medicines using robotic and 3D printing methods, as well as ad hoc printing of the adjusted drug dose for each patient.
Digitalisation also creates opportunities to deliver services around products that enrich the patient experience, for example digital apps to improve diabetes management.

Intelligence and strategy

Regulatory processes, whether at a national or international level (for example, ICH), are continuously evolving. Anticipation and the ability to prepare and adapt for these changes is integral to enabling companies to efficiently manage their portfolio, strategies, and processes.
Digital transformation allows organisations to quickly access and assess information from multiple sources using smart technologies such as NLP and other AI tools to review information. The same approach can be applied to market intelligence, internal intelligence across the portfolio, as well as monitoring social media networks and various forums.

Innovation across R&D

In future, the design of new medicines will be significantly enhanced by digitalisation that will make it easy to leverage internal and external knowledge for new product design. Technologies such as RPA and imaging and simulation tools could help to find new ways and even visualise potential target molecules.
By storing data acquired during discovery in a more structured way, such as the use of electronic lab notebooks (ELNs) can help to streamline future clinical development decisions.
During non-clinical studies, digital approaches such as in-silico pharmacology and toxicology and PK/PD simulation are growing rapidly, which allows companies to leverage data from many diverse sources.
RWE is also helping to support innovative new approaches to R&D. The FDA notes, for example, that product developers are using RWE and real-world data to support clinical trial designs and observational studies to gain insights into new treatment approaches.

Business models

In addition to the industry-specific capabilities digitalisation brings to the life sciences, it also assists in supporting industry-wide business functions, including:
• Improving integration and collaboration with third parties
• Streamlining and harmonising all outsourcing activities to improve quality and total cost of ownership
• Using blockchains to secure data exchange with stakeholders
• Streamlining teleworking


Digitalisation is already transforming the life sciences industry and disrupting the value chain. Pharmaceutical companies, industry organisations, and regulators are committed to take advantage of the promise digital offers to create more effective, data-driven systems that benefit patients. Digital innovation has the potential to transform health and care, enhance regulatory and safety protocols and processes, and allow companies to developing exciting new products and solutions that have the potential to create better outcomes for patients.

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The Journey to Digital Transformation in Life Sciences