To truly understand how to improve operational excellence (OpEx) in the medical devices industry, it is necessary to first understand what the value-add is for their markets. 

Then, companies must understand the regulations, standards, and costs of quality. Without this information, they will not be able to effectively apply Lean manufacturing and operational excellence principles. But how do we get there? This post looks at three key aspects of medical device manufacturing, and how they can be applied to the entire sector.

As the industry continues to undergo unprecedented regulatory changes, mergers and divestitures, and value-based payment models, companies must learn how to improve operational performance. To cope with these challenges, companies apply technology and take advantage of outside managed service partners to handle these tasks. These partnerships offer companies the advantage of freeing up internal resources to focus on core aspects of the business. It is essential to find a partner that understands the medical devices industry and has experience in the field.

Lean in Ireland has led to massive success and has turned the country into a global hub for MedTech. The growing scrutiny from different global regulatory authorities has also increased uptake of organizational excellence. This is because companies are constantly monitoring regulatory bodies in different jurisdictions. However, fear of upsetting regulatory authorities has often slowed down the implementation of change in manufacturing. If organizations don't embrace these changes, they risk losing their customers.

Lean is not a new concept, but the medical devices industry needs to look at it in a different way. Although Lean is commonly associated with the automotive industry, it has been slowly adapted to the highly regulated medical devices industry. The benefits of implementing Lean methods in a highly regulated environment are numerous. For one, Lean is not just about eliminating waste. Lean is about enhanced quality, process capability, process reliability, business efficiency and profitability!
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For more about operational excellence, checkout Top Ten Strategic Decision-Making Tools for Operational Excellence

Related Reading:​

1. Kaizen for pharmaceutical, medical device and biotech industries
2. How to cut costs strategically using Kaizen
3. Streamline processes and workflows with Gemba Walk.
4. Top Ten Strategic Decision-Making Tools for Operational Excellence

Follow Shruti on Twitter, Facebook, YouTube, LinkedIn

Categories: Lifesciences | Operational Excellence

Keywords and Tags:
#operationalexcellence #operationalexcellenceformedicaldeviceindustry #strategicdecisionmaking #strategy  #strategymanagement #decisiontools #decisionmaking #strategicplanning  #challengesofdecisionmaking​

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.
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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.

​Biopharmaceutical R&D involves a series of high-risk and high-investment decisions. In addition, the industry faces considerable productivity challenge in terms of identifying, testing, and bringing new drugs to market, especially in the context of the highly innovative therapies we seek today.

In previous parts of this series, I discussed Introduction to digitalization in pharma and medical device R&D (Part 1), the need for digitalization (Part 2) and how to go for digitalization in pharma and medical device R&D (Part 3).
​
In this blogpost, I shall highlight some of the salient advantages of digitalization in pharma and medical device R&Ds.

​Digital transformation via digitization and digitalization in R&D allows researchers to automate time-consuming manual processes and open new exploration skylines in prickly issues that have failed to evoke breakthroughs.

Artificial intelligence (AI), advanced analytics and automation are changing ways of working in scientific research. The umbrella category of AI and advanced analytics of digital technology has the maximum potential to improve R&D productivity.

Close behind are identification of biomarkers, use of EHRs (Electronic Health Records) and Clinical Registries.

A significant advantage of digitalization in drug development is creation of targeting biomarkers as the therapeutic approach, followed closely by gene therapies and customized therapies targeting specific disease stages & comorbidities.

Digitalization opens pharma R&D horizons in areas such as genomics which further leads to breakthroughs in precision medicine. It also creates opportunities for decentralized clinical trials, unleashing future innovation in digi-ceuticals and healthcare wearables.

In the allied chemicals sector too, R&D digitalization facilitates designing and modeling new materials and composites. Digitalized chemical innovation is the foundation for everyday products from smartphones and fiberoptic network cables to autonomous vehicles. Digitalization enables researchers to better predict the properties of a material, the performance of an active molecule or its toxicological effect.

As quantum computing- an element of digitalization, allows deeper molecular modeling, medical device research and development specialists expect quantum computing to open new material prospects in specialties such as batteries, semiconductors, superconductors, composites and opto-electronic gadgets.

Further, quantum computing-based molecular modelling helps researchers to identify the most effective molecular designs or structures before having to synthesize molecules in laboratory settings. AI helps glean the best compound in the early stage, so researchers can skip over the very long discovery processes. For example- using AI to select or optimize the antibodies and evaluate efficacy or toxicity in the preclinical stage.

Digitalization explores the space of interest for discovery, guides researchers to do more focused experiments and generate data to refine the experimentation process further.

As therapies are designed as targeted dosage forms, the efforts to identify those patients who may benefit most from a drug takes considerable amount of time and effort. Digitalization helps these efforts by leveraging digital technology to help find the right people set for the right trials.

For example- AI improves patient-trial matching by crunching large datasets like electronic health records, genomic data, medical literature, trial databases, inadequate enrollment of patients in trials—too small a sample, too high a drop-off rate, or suboptimal cohort selection. Failing to exclude individuals using another medicine that could interfere with the tested one—is a major cause of trial failure.

Once underway, advanced analytics can enable adaptive clinical trials, where researchers modify a live trial, such as by refining the sample size, changing the allocation of patients to ‘control’ versus ‘trial’ arms, and stopping a trial early based on likely success or failure.

A significant value driver within clinical R&D is reinventing how companies engage physicians, patients, and investigators at a granular level. Through digitalization, the medical affairs teams can understand the requirements of individual physicians (as well as other stakeholders) and to deliver precise information on-demand.

Lowering the costs of trials and improving experimental data are worthy ends in themselves, but companies can also use digital technology to identify new lines of therapy.

For instance, in health care, the quality of data available to researchers helps in the development of therapeutic areas like immunotherapy, which alters the human immune system to better fight diseases like cancer. This is a far cry from current therapies like radiotherapy and chemotherapy which bring debilitating side effects and are often palliative rather than curative. Digital technologies like wearables, implants, and digestible can show how a therapy is working in richer detail via digital biomarkers.

An overarching benefit of digitalization in pharma R&D is improving the quality of new products before they enter the experiment and clinical trial process. Digital innovation can improve the quality of experiments from optimizing design and protocols to generating better data about the drug candidate’s effectiveness.

Big data and AI enabled modelling processes allow researchers to move from static processes to more fluid and adaptable working procedures for drug discovery and R&D pipeline portfolio management.

Moreover, analytics, simulation, prediction, and modeling show researchers more about how an innovation might fare in the real world. This eliminates drug candidates that might once have incurred costs in a failed pilot or pivotal trial due to shortcomings that researchers were unable to spot in an earlier phase.

Further, in a digitalized formulation R&D, with super imposable information from recipe builder on bio-chemical properties of active(s) and additives, enforced patent and regulatory data, with a click of a mouse key, formulators can checkout series of formulation suggestions. These formulation suggestions can be further evaluated by digital experimentation.
​
On an average, post digitalization in drug development, the time from drug discovery thru product commercialization can be decreased by as much as 6 years! 

​A Japanese pharma company (Reference- https://www.bbc.com/news/technology-51315462) put a new drug molecule invented entirely by artificial intelligence into human clinical trials. This new compound is designed to help patients with obsessive-compulsive disorder (OCD). It reached human clinical trials in just 12 months – now, compare that with the four to six years that it traditionally takes for drug candidates to reach that stage! Cool, isn’t it?
​
In the next part of this series, I shall elaborate on- Digitalization in various phases of drug research and development.

​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 5:  Digitalization in various phases of drug research and development.
Part 6:  Selecting the right R&D digitalization platform.
Part 7:  Six building blocks for digital transformation in pharmaceutical and medical device 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.

​Keywords and Tags:

#businessprocessimprovement #continuousimprovement #digitalization #digitization #digitaltransformation #digitaltransformationinR&D  #digitalizationinR&D #continuousimprovementinR&D #advantagesofdigitalization