Innovations in Digital Clinical Trials

It is the distinct ‘specialty’ Products, instead of the high-volume, bestsellers that Pharma companies of millennial era are focusing on. This gradual but revolutionary transition has further widely opened fresh prospects in terms of high-end value-add that these visionary Pharma products have to offer the world.  With product development costs skyrocketing (an estimated average of $2.6 Billion per invention), as well as augmenting drug development complications, Pharma Companies of today are increasingly trying to leverage and tap on high-end technology’s potentials and possibilities.  Innovative digital technology usage help Pharma companies keep abreast with soaring market expectations (from subjects, CROs, Clinical Trial staff etc.).  They also to provide a more customized touch to Pharma products that they develop.  Hence, there has been a mandatory need among the huge-potential Pharma market to focus more and more on technology implementation in drug-development to provide improved patient outcomes.

Complete digitization for revolutionary, out-of-box R&D and Pharma outcomes

Numerous innovative technology tools are available for smart wielding on clinical and drug development processes, and R&D.  Recent statistics released by Academic institutions across the globe clearly attribute, by the year 2020, an approximate 40 percentage of pharma market profitability to digital technology implementations and usage.

In-depth market analysis from AMEEX has further revealed that Clinical Trial and Pharma Experts vouch strongly on implementation and usage of digital technology tools across their domains, as the sole promising emancipator of patient outcomes.  These Organizations have also attributed overwhelmingly strong performances of their R&D set-ups solely on digital technology implementations across departments.

Despite these striking advantages, organizations across the Pharma industry have been rather slow in implementing the right digital technologies for their R&D and other needs.  This can be attributed to their cautious approach, considering factors such as perils in adherence to compliances, ever changing regulatory protocols, eternally evolving technologies, and ROI uncertainties after digitization.

All-inclusive Clinical Trial Digitalization – An AMEEX perspective

The best way to start on digitalization with a broader, insightful perspective, R&D Enterprises require a clear-cut, tactical policy that is perfectly customized and affiliated with various factors influencing their business such as their:

• Scientific field(s) of specialization(s)
• Product/Service Offerings
• Availability of adequate cushioning of occupational risks
• Portfolio Expansion capability
• Keenness in exploring still unmapped Portfolio territories

Innovative digitalized Clinical Trials Vs scrappy take-aways

The digital options available in the current Clinical Trial and R&D market are so vast and diverse. This made Sponsors and Enterprises in the early part of this millennium involuntarily opt for digital options as bits and pieces of their requirements, instead of a steady digitalized implementation across their organization.  Following pages analyze in detail about the shortcomings of current digital Clinical Trial adoptions Vs the integrated, consistent digitalized Enterprise tools.

Clinical Trial Design stage:

Digitalized Clinical Trial tools are characterized by their sheer ease-of-use of Real World Data (RWD) (data from Subjects, social data collections, care models), and Real World Evidence (RWE) (vital inferences from published Trials in Journals) to create a powerful Trial Design right from the early stages of any volume of Clinical Trial.

Effective leveraging of RWD and RWE data to compare between historical trial failure Vs success parameters.

Looking beyond RWD and RWD with a wholistic insightful digitalized style: detect exceptional data contributions from related Sources such as Electronic Health Records (EHR), Forums for patient interactions, wearables etc.

Facilitates thorough analysis and ensuring Subject needs and Trial feasibility options before enrolling Subjects.

Augmented Adaptive Clinical Trial Designs: Such designs help in even intricate practical scenarios at micro level operations such as park attendance, park hours, staff recruitment, performance time setting etc.

Trial Designs more sensitive to Patient and care-giver needs: Focus more on real-time patient data than observations and opinions from consultants, physicians, journals and publications, thus augmenting Trial success rates.

Use of Digital options such as patient websites, live discussion forums, are:
Great Trial time-savers
 Facilitate interaction with broader population of Subjects and;
 Impact greatly on Trial cost reduction

Trial Start-up stage: Digitalized Enterprise consistent options for optimal Trial Site identification and Subject engagement:

Spotting and eliminating low-performance sites using insightful, predictive analytics tools that can powerfully analyze Site’s historical performance data.

Predictive analysis of anticipated number-feasibility of participant to achieve optimized Subject recruitment through tools such as Electronic Health Records that can provide vital insights on inclusion and exclusion criteria.

Avoid inconsistencies in data leveraging through RWE and Site data, and instead wield insightful and powerful data analytics tools to identify Sites, CRAs, CROs, and areas with population having most number of desired nature of Subjects, thus optimizing on Subject recruitment.

Clinical Trial Start-up: Process Automation Tools options for Clinical development for upgraded Stakeholder and Site Staff engagement through Artificial Intelligence (AI) ad Robotics tools, automated Language processing and machine learning tools.

This helps Sponsors selecting quality Sites for Clinical Trials, greatly focus only on value-added activities, and cost-cutting.

Enhanced Trial Site collaboration thrugh usage of remote learning website tools, Digital Applications and Platforms for collaboration with Investigators (CROs, CRAs, Site Staff etc) to deliver precise Subject and Site data.

Usage of powerful common-Platform, multi-channel collaborative Tools: Central access and interactions, with multiple Sponsors, effective collaboration between multiple Clinical Trial processes and Site Staff, thus enabling seamless management of complex and multiple Site Staff and processes.

Statistics have revealed a striking 10% reduction in Site related costs wherever such high-tech digitalization are being used.

Clinical Trial Conduct and Closure: Digitalized Enterprise consistent options for speedy Subject Recruitment Trial Protocol insights and strict adherence and fast database closure:

• Digitalized tools are empirically found to reduce Subject recruitment by about 92%
• Tools and Platforms such as Smart-phone Apps, Social Media, Website-based Subject-interaction Forums have multifold increased scope of effective interaction with Patients, and Clinical Trial Staff
• Patients can make effective usage of such Tools and Platforms to view their relevant Clinical Trial information, Questionnaires etc
• Such tools are so powerful enough to facilitate self-help and selection options for Subjects such as Proteomics, Metobolomics, Geneomics etc
• Such Tools and Platforms have thus greatly augmented Site and Subject selection processes
• Impeccable Attrition Management: Apps and tools based on Mobile and Smart Phone and other wearable devices greatly help Sponsors and Site Staff to micro-monitor participation and Trial adherence of Subjects even remotely.
• These include wearables, digestible trackers, connected inhalers etc
• These facilitate seamless and precise Subject/Participant data-capture, but also improves quality of data captured; they are capable of not missing out even a single vital data, thus eliminating the need for data editing or cleaning
• Such remote data capture and Analytics tools significantly facilitate adherence to Clinical Trial timelines., reduced Clinical Trial Life Cycle right from Subject Visit to data approval and decision-making based on the data

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