Introduction

In today's fast-paced and data-driven world, organizations are constantly seeking ways to improve their processes to increase operational excellence.

Hence, regardless of industry sector, process improvement projects are on the rise, thus keeping project management teams super busy. Therefore, like any other department in an organization, for project management function too, continuous improvement is vital.

One of the key continual improvements in the project management function is digitalization. Traditional project management approaches have served us well. But the rise of artificial intelligence (AI) application in project management is recalibrating the landscape of process improvement campaigns.

Today, AI is not just a buzzword; it's a revolutionary driving force that is set to transform how we plan, execute, and monitor process improvement initiatives. In this blog post, I shall delve into the profound ways AI is redefining management of process improvement projects, and why it's essential for businesses to embrace this transformative technology.

1. Data-Driven Decision Making
AI's primary strength lies in its ability to analyze vast amounts of data quickly and accurately. In management of process improvement projects, this translates to data-driven decision making. You may want to checkout Top ten decision-making tools for operational excellence here.

AI can sift through historical project data, identify patterns, trends and provide actionable insights. This empowers project managers to predict potential roadblocks, make informed decisions and optimize project management effectively, which results in efficient and successful project outcomes. Also, the process improvement projects get handled successfully, within the scope- cost- time outline.

2. Predictive Analytics
Predictive analytics is one of the most exciting AI applications in process improvement project management. AI can forecast potential bottlenecks, resource constraints as well as project risks based on both historical data and real-time information. This facilitates project managers to proactively address challenges before they become major setbacks. By utilizing AI's predictive capabilities, organizations can stay one step ahead in managing projects effectively and efficiently.

3. Automation and Efficiency
AI is a game-changer when it comes to automating routine tasks, especially the repetitive and time-consuming activities. Hence, such activities which tend to bog down project workforce and drain efficiencies can now be assigned to AI-powered tools and bots. This will free-up valuable time and resources for the project team, that can be redirected towards higher-value project management tasks. Automation will ensure that project management processes will run smoother and more efficiently, reducing the risk of human error.

4. Enhanced Resource Allocation
One of the critical aspects of project management is resource allocation. AI can assist in optimizing resource allocation by analyzing project requirements, workforce skills, capability, and availability. It ensures that the right people get assigned to the right tasks, thus improving project efficiency, and ultimately leading to cost savings. Additionally, AI can help to identify over- or underutilized resources, and enable better skill governance and workforce management.

5. Real-Time Monitoring and Reporting
AI-driven dashboards provide real-time monitoring and reporting capabilities, empowering project managers to track progress, identify deviations, and take corrective actions promptly. This level of visibility into project performance enables project managers to make on-the-fly adjustments (without any scope creep), ensuring that projects stay on track and meet their objectives.

6. Personalized Insights
AI can provide personalized insights and recommendations to individual project team members, offering guidance on their specific tasks and responsibilities. This not only improves productivity but also prevents oversight. Also, it motivates the project team and enhances collaborative working. In fact, each team member can create a tailored roadmap for their contribution to the project's success and growth.

7. Risk Management
Risk management is one of the key aspects of effective project management and AI’s ability to swiftly analyze huge amounts of data facilitates in comprehensive risk assessments early on. This allows project managers to take proactive measures at risk mitigation and prevent chances of potential project failures. Further, AI can suggest suitable risk mitigation strategies based on historical data and predictive analytics, thus increasing the likelihood of successful project outcomes.

Conclusion
The impact of AI on management of process improvement projects is undeniable. AI has transformed the way projects are handled end-to-end. From data-driven decision-making to predictive analytics, automation, and personalized insights, AI has equipped project managers with the tools they need to succeed in their tasks. And as AI continues to advance in its role, its impact on project management will get more profound. Therefore, organizations that embrace AI and incorporate it into their project management best practices will gain a competitive edge, delivering higher quality projects more efficiently.

AI is no longer the future; it's the present, and those who harness its power will lead the way in operational excellence.


​Related Reading:​

1. Top Ten Strategic Decision-Making Tools for Operational Excellence
2. Popular Continuous Improvement Workshops & Webinars for Manufacturing Industries
3. What is Machine Learning?
4. Popular Continuous Improvement Tools.

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Categories:   Process Improvement | Operations | Digitalization

Keywords and Tags:
#DrShrutiBhat #ProcessImprovement #ProcessExcellence  #ContinuousImprovement #OperationalExcellence #ProjectManagement #AI #Digitalization #DigitalTransformation

Going digital is the mantra of success in today’s times. Businesses both traditional and progressive must imbibe digital processes to thrive. Also, this digital transformation in organizations is a continuous process, since businesses must keep pace with changing digital technology.

Checkout this video to know more about six key essentials for successful digital transformation.

This video belongs to my YouTube video series- One-minute guide to continuous improvement where I explain various topics related to continuous improvement for operational excellence and business growth.

Watch on …

Are you ready to go for digital transformation at your organization?

Follow Shruti on Twitter, Facebook, YouTube, LinkedIn

1. One minute continuous improvement guide series.

Keywords and Tags-

​#digtaltransformation  #godigital  #digitization  #digitalziation  #continuousimprovement 

Part 3 mentioned- How to go for digitalization in R&D, Part 4 discussed advantages of digitalization, Part 5 elaborated on digitalization in various phases of drug research and development, Part 6 highlighted selecting the right R&D digitalization platform, while Part 7 highlighted six building blocks for digital transformation in pharmaceutical and medical device R&D, while Part 8 touched upon- how to transform existing R&D setup to a digitalized R&D.

In this blogpost I shall share- Tips and Quick wins for digitalization in pharmaceutical and medical device R&D.

Pharmaceutical business has several customer touch points for example- distributors, doctors, healthcare staff, caregivers, and patients (who are the ultimate consumer). Obtaining VOC is vital in any continuous improvement campaign, same with digitalization. Install suitable mechanisms to obtain feedback via surveys, interviews etc. Note that such feedback must be gathered periodically to ensure that digitalization campaigns run smooth, error-free and rapid as planned.

Tip: Transition to digitalization is often more complex than anticipated. Some roadblocks on the digitalization transition aren’t apparent until it’s under way.

Note that, continuous improvement in pharmaceutical and medical device R&Ds can happen via 15 different pathways. Digitalization is just one such continuous improvement pathway.

Digital is a journey and organizations can anticipate both false starts and quick wins. Even being a fast follower, which by definition requires the ability to move quickly can be elusive.
 
Organizations with serious intentions of moving quickly could find themselves lagging behind as unexpected challenges set them back. Those that have not yet started could find themselves on the back foot when others demonstrate success.
 
Digital transformation in drug industry presents the opportunity to ensure better outcomes for patients via targeted therapies, significantly reduced cost of drug development and accelerated cycle times to get treatments to patients faster.

Digitization and digitalization are not something companies can debate on to have or have not. It isn’t about building a competitive advantage or a core differentiator – it is about staying relevant in business in the very near future.

To make it successful, it is less about where you start than about where you want to go. So, make sure you have a vision for going digital and that the pilots and initiatives you run tie back to it and can help it scale.

Digitalization is a continuous improvement process. Hence, organizations must keep pace with advances in digitalization technology along with advances in pharmaceutical sciences, market dynamics and more importantly patient needs.

Continuous improvement in R&D be it via digitalization or any other pathway is a top-down initiative. Leaders must make continuous improvement in pharma or medical device R&D a priority and an integral part of corporate goals.
​
Digital transformation can drive success in achieving key strategic R&D imperatives. However, the drive to digitalize needs to come from the C-suite or senior R&D leadership.

R&D digitalization involves big cost (although few phases of digitalization can be done on a shoe-string budget). But it is the need of the business to stay relevant and stay competitive. Hence, companies must strategically plan their digitalization journey.

Adopting a digital mindset is thus a new business imperative. A comprehensive R&D strategy is critical to enable companies to move and process large amounts of data effectively to make data-driven scientific and business decisions quickly and accurately to generate evidence in support of future product value propositions. This will require new capabilities; new skills sets and new leadership mindset.

Digitalization will be a necessity in pharma/ medical device R&Ds in years to come regardless of whether it is an innovator company or a generic player. The extent and magnitude of digitalization needed of course shall be different.

Digitalization in R&D will definitely bring a positive change in working of the R&D department, and its ripples of impact will be seen across all departments within the organization. Therefore, it is crucial that this digital transformation is smooth, does not adversely impact the top line and bottom line while the change is happening.
 
The best way to begin digitalization initiative is to start with Kaizen.
 
Kaizen is a time-tested Japanese technique of business transformation and change management. The spirit of Kaizen involves small changes done continuously over time to reap exponential rewards.
 
Organizations could do Kaizen-ing to build digital strategy as well; but Kaizen certainly must be used during the digital strategy execution phase. You can know more about Kaizen for Pharmaceuticals and medical devices industry here.
 
Conduct multiple Kaizen events to navigate your digital transformation journey successfully.
 
The future of pharmaceutical R&D ten years ahead as I foresee is an entirely new panorama: a world where drug discovery is driven by machine learning and advanced analytics mining large data sets, enabling us to understand and visualize interaction with targets and to predict in silico a molecule’s likelihood of success, meet approval and reach market.

Done right digitalization, the size of the opportunity could be $50–150 billion of EBITDA across the industry.
 
Note that there are fifteen different Continuous Improvement pathways for pharmaceutical and medical device R&Ds. Are you planning a Continuous Improvement initiative for your R&D division? 

​Keywords and Tags:

#continuousimprovement #digitization  #digitalization #kaizenforpharmaceuticals #digitaltransformation #digitalizationinpharmaceuticalindustry  #kaizenindigtaltransformation

As organizations launch digital initiatives, process owners, executives and the company’s management board must monitor digital progress. 

That is, whether ‘digital’ is delivering desired results. They must have full view and influence across business functions to ensure that the organization as a whole is leveraging digital in a meaningful and profitable way.
 
The series so far- Part 1 of this series introduced digitalization in pharma and medical device R&D, Part 2 discussed the need for digitalization, Part 3 mentioned- How to go for digitalization in R&D, Part 4 discussed advantages of digitalization, Part 5 elaborated on digitalization in various phases of drug research and development, Part 6 highlighted selecting the right R&D digitalization platform, while Part 7 highlighted six building blocks for digital transformation in pharmaceutical and medical device R&D.

Continuing further with the series, in this blogpost, I shall briefly touch upon- How to transform an existing R&D setup to a digitalized R&D.

At the outset, define success metrics.
​
Defining success metrics is a must for any continuous improvement initiative, same goes for digitalization.
 
Here are top 6 broad markers of digital progress-

1. Return on digital investments.
2. Percentage of annual technology budget spent on digital initiatives within the organization.
3. Success with minimizing time to market new products i.e. are you getting ahead of your competition?
4. Percentage of leader’s incentives linked to digital initiatives.
5. Top technical talent reskilled, recruited and retained.
6. Customer feedback.

 
Digital is simple, right? Not quite. The million-dollar question is: where to start?

Technologies like AI (artificial intelligence), Big Data and Advanced Analytics have huge impacts on the productivity of R&D. But harnessing the full potential of these new technologies will require significant organizational change.

I shall discuss some avenues to trigger your R&D digital transformation in order to stay relevant in the near future. 

Pessimism, cynicism, reluctance, disbelief, doubt, legacy systems, rusty processes and change rebels are just a few hurdles Continuous Improvement and R&D leaders will have to overcome in quest for R&D digitalization.

If one were to analyze various digital transformation success stories, all of them  share one point in common: Resilience. Those digital transformation campaigns succeeded by pulling champions together to distil the essence and power of digital in their own business function or a pilot function to build on the ‘quick wins’. Digital champions owning individual pilots then catalyzed the overall digital transformation across the organization.

Before pursuing digital opportunities, Continuous Improvement and R&D leaders must first develop and align on a digital vision for their organization, by looking at both the overall digital strategy and value proposition for their companies. They should begin by assessing their organizational capabilities, estimate the required resources, and contemplate potential partnerships that could help them achieve their goals.

The basic question underlying all strategic plans is: How can digital help us transform core business processes or generate new opportunities?

Transformation to digitalization begins with- Vision, followed by value stream mapping, process mapping, product life cycle mapping, new product strategy mapping, VOC (voice of customer) survey, selecting the most- appropriate R&D digitalization platform, digital strategy roadmap and managing change.

R&D digitalization is just the beginning.

Digitalization is a continuous improvement process. Therefore, organizations must keep pace with advances in digitalization technology, along with advances in pharmaceutical sciences, market dynamics and more importantly changing patient needs.

In the next part of this series- Part 9, I shall highlight tips, quick wins for digitalization in pharmaceutical and medical device R&Ds.

​Meanwhile, note that there are fifteen different Continuous Improvement pathways for pharmaceutical and medical device R&Ds. Are you planning a Continuous Improvement initiative for your R&D division?

​Keywords and Tags:

#continuousimprovement  #digitalization #digitalizationinpharmaceuticalindustry #markersofdigitalization

Part 1 of this blogpost series introduced digitalization in pharma and medical device R&D while, Part 2 discussed on the need for digitalization.

Part 3 mentioned on- How to go for digitalization in R&D, Part 4 discussed advantages of digitalization, Part 5 elaborated on digitalization in various phases of drug research and development, while Part 6 highlighted on selecting the right R&D digitalization platform.
​
Continuing the series, in this blogpost I shall discuss on- Six building blocks for digital transformation in pharmaceutical and medical devices R&D.

The six building blocks of digital transformation are as follows:

1. Vision: Develop a digital vision for the organization while always considering the impact on stakeholders/ distributors/ customers.
2. Developing and upskilling talent: Identify talent needs and strategies for filling gaps. Create new organizational structures to integrate digital talent and leverage digital learning programs, technology and external sources to develop talent. It is also important for companies to create a new organizational structure and deployment model to integrate any new digital team member into the organization.
3. Agile working: Rapidly test digital initiatives and make revisions based on insights gained from the field. Companies must create an Agile environment that makes it possible to test new approaches or technologies quickly and then iteratively make improvements based on customer feedback, all while managing risks.
4. New technology: New technology capabilities form the foundation of any digital transformation. Create new technology that covers areas including commerce front ends and integration architecture. As organizations evaluate their applications and data infrastructure, they should identify gaps that might prevent them from achieving their digital vision and linked potential opportunities.
5. Data use: Consider data related issues in strategy road maps such as architecture requirements and identify specific use cases that will benefit from analytics.
6. Driving the adoption and scaling of digital initiatives: Scale change across the organization with a focus on product, service, commercial strategy, execution, customer service, experimentation, transactions etc.

 
The above six parameters apply to digital transformation initiatives in general and also to digitalization in pharma and medical device R&D. Once the digital building blocks are taken care of, the next but one of the most important challenges of digital transformation is transition from existing analog working to going digital.
 
Coming up in the next part of this series- How to transform existing R&D setup to a digitalized R&D!

​Meanwhile, note that there are fifteen different Continuous Improvement pathways for pharmaceutical and medical device R&Ds. Are you planning a Continuous Improvement initiative for your R&D division?

Part 8:  How to transform existing R&D setup to a digitalized R&D.
Part 9:  Tips and Quick wins of digitalization in pharmaceutical and medical device R&D.

Part 1 of this blogpost series introduced digitalization in pharma and medical device R&D, Part 2 discussed on the need for digitalization.

Part 3 mentioned on- How to go for digitalization in R&D, Part 4 discussed advantages of digitalization in pharma and medical device R&Ds, while Part 5 elaborated on digitalization in various aspects of drug research and development.
​
In this blogpost series I shall discuss on- Selecting the right R&D digitalization platform.

This totally depends on the company’s critical needs and its position on the transformation cycle. Another important factor is data pipeline. For example-

• Does your company conduct drug discovery research?
• Does it develop innovative products or generics?
• Which therapeutic areas are considered for product development?
• Does your product pipeline entail drugs for humans or veterinary?
• Does it use advance data science currently or is all work done only in analog mode?
• How much of information must be shared with other technical/ non-technical departments within the organization?

R&D digitalization surely involves a huge cost. But it is the need of business to stay relevant and stay competitive. Hence companies must strategically plan its digitalization journey.

​Continuous improvement in R&D via digitalization or any other pathway is a top-down initiative. Leaders must make 'continuous improvement' in pharma R&D a priority and an integral part of corporate goals.
​
There are scores of R&D digitalization platforms out there. Selecting a platform which is right for your company is key. So, what are some of the salient features to note while choosing R&D digitalization platform? 

1. Position of the company in the overall digital transformation cycle.
​
2. Compliance to regulations:
Compliance to 21 CFR Part 11, ICH and all regulations impacting your product, R&D management and line of business. Also, compliance to testing, labelling and/or other product-specific regulations for drug/ drug product.

3. Product pipeline:
Developing now and what is the company aiming for? What are the types of formulations a company wants to offer in their product mix? Is it a synthetic small molecule, herbal, peptide or some other biological product, vaccine, medical device, diagnostic etc.?

Is it multiple types of dosage forms? Because a single digitalization platform should be able to cater to all needs. Which markets are you developing the products for? Because the digitalization platform must build products to comply with all regulations (concerning development, testing, labeling and other product-specific guidelines) for each market.
​
4. Talent building:
Talent building via employee re-skilling and/or recruitment. A bottom-up approach to changing skills and mindsets. Make Agile work in a practical way. Build capabilities and team-member engagement.

5. Facilitates remote working and/or working in Cloud.

6. Compatibility and inter operability of the platform with existing digital ecosystem within the organization:
Compatibility and inter operability of the platform with existing digital ecosystem within the company such as LIMS, ERP supply chain software, BMS (building maintenance software), equipment process automation software etc. 

Compatibility and inter operability of the platform with customer engagement software channel with healthcare professionals: The med tech industry is shifting from a model that revolved around sales rep to an omni-channel world, in which HCPs (Health care professionals) are able to access information as and when they need. Although reps remain the main point of contact, companies are augmenting this relationship with new resources & tools and coordinating them across channels to address stakeholder’s needs.

Compatibility with digital marketing, portals and e-commerce platforms: 
​According to a published statistic, 80% of med tech companies shifted more than 20% of their marketing expenditures to digital channels in 2020. Further, 2/3rds of med tech companies expect online channels to account for more than 20% of their revenue by 2025. 

Omni-channel engagement is not about making tweaks to existing models. It is about shifting to a new model in which Agile teams bring design thinking, digital engagement and analytics to help sales rep deliver the right message at the right time through the right channel to the right stakeholder.

In the next part of this series, I shall discuss on- Six building blocks for digital transformation in pharmaceutical and medical devices R&D.

​Meanwhile, note that there are fifteen different Continuous Improvement pathways for pharmaceutical and medical device R&Ds. Are you planning a Continuous Improvement initiative for your R&D division?

Part 7:  Six building blocks for digital transformation in pharmaceutical and medical devices R&D.
Part 8:  How to transform existing R&D setup to a digitalized R&D.
Part 9:  Tips and Quick wins of digitalization in pharmaceutical and medical device R&D.

Realizing the digital opportunity is no simple task—it represents an innovation capability for the entire organization- as good as an organizational overhaul. 

​Part 1 of this blogpost series introduced digitalization in pharma and medical device R&D, Part 2 discussed on the need for digitalization, Part 3 mentioned on- How to go for digitalization in R&D, while Part 4 discussed advantages of digitalization.

In this blogpost, I shall elaborate on- Digitalization in various phases of drug research and development.

Experiments and clinical trials carry a huge cost for drug industries, both financially and in terms of human and scientific resources. Advanced simulation, modelling, AI-based analytics, and quantum computing help identify the strongest candidate for new therapies by allowing only the most promising moieties to proceed to the costly experimental phase. 
​
Let’s see how does digitalization impact various phases of drug development…

​Traditionally new drug discovery used mouse models with a hope that findings would translate to humans, leading to high failure rates. Now and going forward new drug moieties are discovered using human genome sequencing technology. Rapid growth in genome sequencing technology allows researchers to not only design therapies based on human biology, but also at reduced costs.

Using digitalization at in silico discovery for target identification maximizes the value of data. The efficient data interoperability implies a clear data strategy, data governance and data management which shrinks drug discovery timelines significantly by 3-5 years! Also, this reduces cost of drug discovery by several million USD.

Further, besides researchers, peers and colleagues from project decision-making to portfolio management & risk optimization functions work more closely together and feel more empowered through increased data visibility and decision transparency.

​Digitalization uses Big Data for formulation prediction. Using digital mode of drug product development shrinks both development cost as well as time enormously.

Just as drug discovery, digitalization impacts how drug products are developed such as-
​
1.      (Drug) Salt- finding study.
2.      Dose-finding study.
3.      Identifying ADME (Absorption Distribution Metabolism Elimination) of the drug.
4.      Route-finding study-

Route finding study identifies the best way to administer the drug or whether the drug can be administered via multiple routes? Should the drug be administered only by per oral route or can it be administered via other mucosal routes such as nasal, inhalation, ophthalmic, parenteral, transdermal etc.

5.      Proof of concept study/ Formulation development & analytical testing-

Digitalization allows machine learning algorithms to review raw material properties such as- drug molecule chemistry, excipient chemistry, powder dynamics, rheology, ADME , patent and regulatory data etc. to build formulation recipes and predict results. Digitalization uses Big Data to suggest formulation compositions.

For instance- in case of targeted drug delivery systems, the choice of carrier is vital. And researchers conduct studies to identify if the carrier-mediated drug transport additive should be- Niosomes, liposomes, methacrylates, ion-exchange resins, cyclodextrins, fullerenes or nanotech-buckyballs, RBC (red blood cells) or something else.

Another customary study is to find out if the formulation requires a therapeutic platform for delivery.

Needless to say, huge number of experiments get done to arrive at the ‘best’ carrier for drug delivery. Obviously, this involves huge R&D cost and time which can be saved by digitalization in product development.

Moreover, data visualization helps researchers to identify the product with best profile. Both in vitro and in vivo data can be visualized. Researchers can skip pilot BE studies if a product shows superimposable data graphics with RLD (reference listed drug). Imagine the costs saved!

Additionally, quantum computing also immensely helps product development via 505 (b) (2) pathway.

Hence, I would say if a company aims to develop products via 505 (b)(2) pathway then digitalization is the way to go. For such companies, digitalization shall save millions of dollars of R&D budget and in addition provides first-mover advantage.

​Digitalization makes clinical research more efficient. Even though electronic data records are standard since long and digital regulatory submissions are being accepted for over two decades, clinical development still has significant untapped efficiency reserves. Discovery and clinical trials making up the largest share of costs to get a drug to commercialization, efficacy gains in these areas therefore have a direct measurable impact not only with time to market but also in real savings.

AI has many potential applications in clinical trials both near- and long-term. These range from automating routine study data entry functions, to analyzing electronic health record data to find suitable candidates & clinical trial sites, to monitoring and encouraging patient compliance with study protocols, to adaptive dose finding, to discovering and modelling potential new molecules and therapies. 

Big Data and real-world data (RWD) are becoming increasingly prevalent as digital devices become more adept at capturing myriad signals from patients in a variety of settings.

For example, combining historical information from EHRs (electronic data records) with imaging, genetic and molecular test data is driving the development of highly targeted oncology treatments, such as CAR-T and other cell therapies, giving hope to patients resistant to more conventional treatment approaches .
 
If Big Data is the raw material of digital transformation, then AI is the engine that sponsors rely on.

AI powered capabilities viz pattern recognition, evolutionary modelling etc. are essential to gather, normalize, analyze and harness large data sets that are fundamental to modern therapeutic development. Also, these models are especially useful for conducting smaller studies that are gaining importance in targeted smaller patient populations.

Additionally, applying advanced statistical models to the new data also improves pharma R&D productivity.

One of the main hurdles in clinical operations is the disconnect between clinical development plans and clinical trial protocols. In other words, between strategy and the operations.

Digitalization defines the ideal trial avatar and guides researchers on patient-centric clinical development,  feasibility of the study to help them better plan the duration of recruitment and trial length, collaborate with patients in the research process, ease patient access, reduce the burden of trial participation and transform patientcare during clinical trials.

Such gained efficiencies, optimize time and cost, expedite patient enrolments, improve retention & increase study diversity, improve investigator productivity, reduce manual effort on repetitive tasks and transform patientcare during a clinical trial by paper-less tracking.

A published case study (Reference- https://www2.deloitte.com/us/en/blog/health-care-blog/2018/how-a-digital-rd-strategy-can-improve-clinical-trial-innovation-and-execution.html) indicated how digital transformation of a standard neurological test reduced clinician burden- in neurological assessment, a commonly used symbol-digit modalities test asks a participant to match basic numerals to geometric shapes according to a reference key. The lower the number of correct connections within the allotted time, the higher the level of cognitive impairment. A biopharma company made this test available to patients on an iPad at the point of care and fed test results directly into the patient’s EHRs. This eliminated the need for clinicians to spend time on conducting the test and entering data and also enabled more standardized test administration.
 
From understanding disease onset and progression to identifying early safety signals or food and drug interactions to engaging with patients for clinical trial participation and awareness to virtual augmented reality to conduct virtual clinical trials, digitalization enables researchers to better predict the properties of a material, the performance of an active molecule and/ or its toxicological effect.
 
In addition, digitalization improves efficiency of post-marketing pharmacovigilance and patient safety.
 
In fact, from now on in the coming decade, adopting digital technology at scale viz patient reported outcomes captured using mobile devices, digital assistants and voice recognition to virtual augmented reality (AR) to conduct virtual clinical trials and digital biomarkers as primary endpoints might just be the norm!

Digitalization will be a necessity in pharma R&Ds in years to come regardless of whether it is an innovator company or a generic player. The extent and magnitude of digitalization needed of course shall be different for the two.

Pharma, medical device R&D digitalization surely involves a huge cost. But it is the need of business to stay relevant and stay competitive. Hence companies must strategically plan its digitalization journey. One of the critical aspects of R&D digitalization is selecting the right digitalization platform.

Coming up in next part of this series- Selecting the right R&D digitalization platform!

​Meanwhile, note that there are fifteen different Continuous Improvement pathways for pharmaceutical and medical device R&Ds. Are you planning a Continuous Improvement initiative for your R&D division?

​Part 6:  Selecting the right R&D digitalization platform.
Part 7:  Six building blocks for digital transformation in pharmaceutical and medical devices R&Ds.
Part 8:  How to transform existing R&D setup to a digitalized R&D.
Part 9:  Tips and Quick wins of digitalization in pharmaceutical and medical device R&D.