Moving Beyond R &D Services; The Rise in Next Generation Technology

Moving Beyond R &D Services; The Rise in Next Generation Technology

Research and development services are on a constant trajectory of evolution. This constant transformation is fueled by new world challenges and new-age technology that keeps on shifting the horizon of what’s possible. As we hurtle toward the sixth generation R&D Services, we cast our focus on what is and will emerge from that horizon. We’ll look through the rise of next-generation technology and how these exactly are shifting the goal post of R&D while taking it to the next level. 

Collaboration on a mammoth scale with cloud technologies  

Cloud computing is not new news. It has been around since the 1960s. While many industries have taken to building atop the backbone that is the cloud, similar adoptions in R&D services haven’t been quite as steadfast. 

The turning point was the coronavirus pandemic that, out of the blue, instigated an immense need to collaborate and share information globally and with swiftness. As an essential enabler, cloud technologies are now rightly setting the pace for coordinating research and data sharing.

Next-generation R&D strategies are leveraging cloud computing in several promising and creative ways as follows: 

  • Merging different types of data such as real-world hospital data and clinical data. The goal is to ensure a more unified and expansive approach to research, thus improving personalization and turnaround 
  • Big data mining allows research labs to store unlimited data on the cloud, while advanced analytics unlock priceless insights from this data
  • Delivering bonus value through integration with other technologies such as IoT to streamline research coordination even further. 

Today, 6 in 10 R&D labs are reliant upon the power of cloud computing in one way or another. This meteoric rise of the cloud will continue to shape the future of R&D services. Cloud computing will undoubtedly be put to even more use by research labs, given that McKinsey finds that the US healthcare sector stands to improve revenue by over $100 billion by leveraging big-data strategies. 

Predictive modeling to make amends in clinical trial intelligence 

Machine learning and artificial intelligence will not just be put to work to automate mindless and repetitive tasks. More importantly, they could be at the forefront of pharmaceutical R &D services innovation. 

As we speak, companies are already bringing predictive analytics into the fold for drug discovery and development in the following ways: 

  • Early failure discovery: Clinical research is typically an unsuccessful affair for most companies with just a 14% success rate. Predictive analytics could offer perspective into market demand, drug adoption success, composition transformation, and much more. Overall, this will mean better risk mitigation.
  • Site health identification. More than 66% of clinical trials fall short in terms of subject enrollment. With a combination of classification techniques & historical pharma data analysis, researchers can discover hindrances or facilitators of site health and thus optimize site selection
  • Anticipating the effectiveness of drugs. Just 1 out of 10 new drugs makes it through regulatory approval and testing. Predictive analytics and survival analysis in particular are essential to increasing those odds by forecasting drug effectiveness and an exact point of failure, should there be one.

Beyond the actual lab, machine learning can also play an important role in managing and improving the sales pipeline. An aspect of R&D that currently troubles approximately 44% of all companies, according to the confessions of top pharma executives. 

3-D modeling for streamlining medical device prototyping

Set to surpass 718 billion by 2023, and with an estimated value of just over 495 billion in 2021, the medical device market is a highly lucrative field. It’s no wonder that many companies are channeling lots of resources and effort into developing cardiac implant monitoring solutions.  

Different research labs have different procedures for device design, testing, and prototyping. The traditional methodology is usually reliant a great deal upon microcontrollers such as Arduino and open-source electronics platforms at large. 

While that is not going to change anytime soon, one particular aspect of medical device prototyping, namely the design phase, could see an increased taking to 3-modeling technologies as a complementary design solution. As a result, this may mean more: 

  • Better quality assurance
  • Improved device functionality
  • Better understanding of material feasibility
  • Product efficiency, etc. 

Moreover, 3D modeling is also enabling medical device personalization according to patient-specific parameters and further gaining traction for patient/researcher education as well as medical training. 

Stretching the frontiers of innovation with R&D IoT

IoT or, The Internet of Things, has exploded within the past decade or so. The IoT healthcare market is set for 17.8% growth between 2023 and 2028,  a huge improvement from a present market value of over $127 billion.

For years, IoT has made inroads in many other industries. In that time, IoT & pharma R&D have long been thought of as a match made in heaven, but the technology is now truly coming of age for clinical trials. 

Here are a few ways IoT is advancing research & development as we know it: 

  • Revolutionizing data. Clinical research relies heavily on data. The conventional way of operation largely runs on static data but IoT is changing that through dynamic data processing and acquisition.
  • Process management. IoT can further help clear out redundancies that afflict the R&D process and even take out manual tasks from the equation through automation. Ultimately, this means faster time-to-market.
  • Devolving clinical trial data collection: R&D players are also turning to IoT devices such as mobile phones and others to gather biometric data without having the patient restricted to the site. This is unlocking a real-world environment that’s improving the success rate of clinical trials.

In addition to facilitating innovation and reducing various errors and inefficiencies, IoT-driven R&D is also predicted to have a huge financial impact. This combination could result in tremendous cost-saving benefits in R&D. 

Require assistance with your clinical R &D?

For over 20 years, Techindia has provided R&D support and cardiac event monitoring services to empower ground-breaking research that’s changing lives for the better. We are here to shore up data collection, subject monitoring, and other nuts and bolts that can hamper your chances of success with your clinical trial. Remember, up to 90% of drug development fails, and that’s why you need all the expert help you can get. What next-generation technologies do you think will shape the future of R&D services? Let us know in the comments. 


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