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Discovering tomorrow's global healthtech trends today

intech.media

Discovering tomorrow's global healthtech trends today

10 Pharma Tech Trends That Will Shape 2021

2020 was the year that pharma tech became front-page news. Politicians, pundits, and people in the streets suddenly became epidemiologists with strong opinions on things like drug trial methodologies and PPE best practices.

But the question on everyone’s lips was: when will we have a vaccine? The interest in a vaccine has, for many people, demystified the drug development process. The public has a better understanding than ever of the rigors involved in drug discovery, trialing, and distribution. They’ve also had a glimpse of the extraordinary technology behind the scenes.

Those of us in the industry are well aware of the scope and reach of digital transformation. Pharma tech has touched every part of the industry, from research to manufacturing to marketing. And this is only the beginning. 2021 promises to be the early stages of a technological revolution that will change the entire sector forever.

The 10 Trends to Watch in 2021

Pharma tech moves quickly, with new products coming to market all the time. But there are some emerging trends that seem likely to shape the next few months. Here are the main ones to keep your eye on:

1.The Covid-19 Aftermath

The race for a Covid-19 vaccine may go down in history as the pharma industry’s Manhattan Project, with the world’s best minds all collaborating on a single project.

We know from history that this great effort will have inspired innovation in labs and meeting rooms everywhere. People have had breakthroughs that will have industry-wide implications, and these discoveries will cascade out in the coming months. It means that it is a vitally important time for industry leaders to watch out for new best practices, new methodologies, and new technology

The ripples of Covid-19 will be felt throughout 2021 and beyond. In the meantime, we can already see ways that this event has reshaped our industry. Research by McKinsey identifies some tech challenges that pharma companies will face in the coming years, such as:

  • Supply chain: Covid-19 exposed a number of issues in the supply chain industry. Manufacturers and distributors will need to improve accountability and transparency while working to strengthen resilience.
  • Working practices: For employees, remote working is here to stay. Employers have to facilitate this transition while keeping an eye on productivity and cybersecurity.
  • Data-driven decision making: Companies need to centralize and standardize their data sources to improve analytics. This will provide the basis for better decision-making based on real-time data.
  • Digital patient interaction: Patients are avoiding the clinic and are instead switching to telemedicine and other forms of digital healthcare. Pharma companies need to understand their role in this new patient-doctor relationship.
  • Amended regulations: The upheaval will lead to a review of regulations, including HIIPA and data privacy laws. Compliance teams need to monitor developments and think about digital solutions to regulatory requirements.Virtual Care,Covid-19

There is no way of predicting the fallout of Covid-19. However, one thing we do know for sure is that there’s no going back to the way things were. This will be a time of great change, and the winners are the ones who can adapt fastest.

 

2.Digital HCP Engagement

Covid-19 has had a double impact on healthcare providers (HCPs). Covid-19 has made a lot of their patients very ill, either directly through infection or indirectly through disruption to medical procedures. Meanwhile, HCPs have been forced to limit patient interactions and switch to solutions like telemedicine. According to Accenture’s research, HCPs reported a 78% drop in patients visiting their practice during the Covid-19 crisis.

This has created an opportunity for many pharma companies to rethink the way that they engage with HCPs. The visiting rep is already in danger of becoming a thing of the past, with 87% of HCPs saying that they want to stick to virtual meetings even after the pandemic ends. Pharma reps can now reach out to doctors and decision-makers over Zoom and Facetime, which will help to cut costs.

But it also raises the issue of how to break through the digital noise and connect with HCPs. Face-to-face communication is a major factor in sales and relationship building. When sales reps are forced to interact digitally, it may impact their ability to forge those bonds with doctors and other decision makers.

Even though HCP engagement is going digital, the key to success might be the human touch. One concerning statistic is that 57% of HCP’s feel that pharma reps don’t fully understand how much Covid-19 has impacted their business. Pharma reps will have to use empathy, communication and creative messaging to connect with HCPs and build lasting partnerships for a post-Covid world.

3.Text mining with NLP

The healthcare sector is sitting on one of the most enormous caches of data in the world. We have access to decades of detailed records, including trial notes, research proposals, and patient data. PubMed alone currently has over 30 million publications, and that number is growing every year. But even in a well-ordered catalog like PubMed, researchers can struggle to find relevant data. That’s where NLP comes in.

Natural Language Processing, or NLP, is a branch of machine learning that deals with the interpretation of language. Human language is a confusing mess from a computer’s perspective, filled with inconsistency, ambiguity, and redundancy. That’s why a basic text search will often return irrelevant results while missing out on relevant documents. NLP uses self-improving algorithms to interpret the meaning behind phrases in English and other languages, allowing for much more complex searches. Using NLP, an R & D team could explore the archives to find papers describing previous trials with similar criteria. Armed with this research, the team can focus on what works, avoid past mistakes, and deliver results in a shorter time.

NLP only works if it has access to data. In terms of pharma tech, this may require a rethink of the way that they create and store documents. While many companies have already begun full digitization, everyone will need to find ways to further centralize and standardize all records.

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4.AI-driven Drug Research

Artificial Intelligence has come on in leaps and bounds over the past decade. In 2015, the AI firm Atomwise partnered with IBM and the University of Toronto to develop an effective treatment for Ebola infections. Atomwise’s algorithms performed high-speed analysis on known compounds, and they identified the most effective ones in record time.

The next few years of AI development may follow along these lines, with pharma companies partnering up with independent AI firms. AI tools can perform tasks like identifying molecules, screening compounds and simulating tests, and it can perform thousands of operations in a small amount of time. This allows researchers to set wider criteria for research projects. They can then use AI to explore a wider range of possible solutions and get fast results.

AI can also perform extremely fine-tuned analysis on an enormous level that would not be possible with a more manual approach. One current application of AI in pharma is the work by Berg LLC. Berg use AI tools to study tissue samples from patients at different stages of disease progression. AI tools can create an astonishing 14 trillion data samples from a single sample, and it can then compare those data points to other tissue samples along the progression path. Berg’s system then compares these results to information obtained from published papers, using NLP techniques.

Of course, the dream is fully AI-driven drug design: you give the problem to a computer, and the computer designs a pill for you. Even if AI does reach this level of competence in the near future, you’ll still face one massive obstacle: as it stands, any drug discovered solely by AI is considered public domain.

5.Virtual Drug Trial Subjects

Drug trials are problematic in many ways, from unreliable results to the many ethical issues. Some researchers are working around this problem with the organ-on-a-chip solution, which involves cultivating tissue from a specific organ such as the lung. Harvard researchers are working on the human-on-a-chip project, which will create a full library of organs on chips.

But another approach may not involve living tissue at all. In Silico testing is entirely simulated on computer. You test digital compounds on a digital human body and get real-world results. With virtual drug trials of this kind, pharma companies can conduct thousands of human trials in seconds, all without jeopardizing a single person or animal’s wellbeing.

Of course, this kind of testing is only as good as the digital models available. Several companies are working on models for a virtual human, such as HumMod, whose model is based on over 5,000 medical papers.

These models use a mix of AI and data analytics to build a fully-functional representation of a test subject. For this reason, the efficacy of these models depends on the volume of available data. Over time, these models will become increasingly precise and detailed, which may allow pharma companies to perform extensive in silico trials before they begin the first round of human testing.

perfectly positioned to take advantage of the next wave

6.Smart Supply Chain With 5G and IoT

Internet of Things (IoT) has been a huge part of the pharma sector for a while now. IoT devices are in vehicles, manufacturing facilities, and even worn by employees. All of these devices transmit vital logistic data that keep your operation running smoothly. For example, suppose a refrigerator breaks on a truck in transit. In that case, an IoT device might raise the alarm about rising temperatures. Someone can then fix the refrigeration issue before the delivery is ruined.

So far, the biggest problem with IoT has been the sheer volume of data produced. There were seven billion IoT devices globally in 2018. By 2025, that will rise to 22 billion. This presents a huge challenge to the existing data infrastructure, especially when so many devices are trying to connect over mobile data. There’s also the issue of how to connect and pass data back to the server. Many IoT devices are relatively basic and only exist to serve a single function, such as returning a temperature or a weight. They don’t have complex operating systems that allow them to navigate a mobile data network.

5G is the missing part of the IoT puzzle. 5G is designed for single-purpose IoT devices to perform fast, reliable transactions with their servers. So, a delivery truck may have dozens of IoT devices that return data about everything from temperature to tire pressure. Production facilities will have thousands of devices that tell you about stock levels, productivity and failures.

All of this data will allow you to create a truly smart supply chain, optimized from end-to-end. You’ll then be of supply chain pharma tech, such as autonomous delivery vehicles.

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7.Next-gen data analytics

Pharma is about to be transformed by a wave of disruptive pharma tech that all have one thing in common: they generate vast quantities of data. IoT produces five quintillion bytes of data every day. To realize value from such extraordinary quantities of data, you’re going to need a whole new approach to data gathering.

Gartner’s annual report on data trends includes some items that are highly relevant to the pharma industry. Some things to note include:

  • No more dashboards: When you mention analytics, most leaders think about the dashboards that they have to check each day. But dashboards can be constraining and often make assumptions about the underlying data. Gartner predicts that dashboards will start to die out and instead give way to Data Stories. These are detailed narratives that will help leaders understand exactly what the data is trying to tell them.
  • Decision intelligence: If dashboards die out, our existing ideas of Business Intelligence will go with them. Instead, we’ll move towards a Decision Intelligence model where AI and data analytics will present leaders with detailed scenarios and potential outcomes modeled on known variables.
  • Augmented data: Pharma companies deal with vast quantities of unstructured data each day. AI processes will help to structure and augment that data into something that can be used by analytics. NLP is one example of this. When NLP “reads” a document, it can generate a set of structured metadata, and this metadata can improve your data analytics.
  • Increased cloud migration: The cloud is essential for Big Data. Cloud storage is secure, scalable, and gives you access to processing resources for complex analytics queries. As pharma companies become increasingly reliant on AI and analytics, they’ll likely move many of their remaining on-premise systems over to a cloud provider.
  • Enterprise blockchain: 2021 may be the year that pharma begins adopting the blockchain as a primary data storage tool. Blockchain has many advantages, like making all data traceable back to its original source.

Data is the foundation for all emerging pharma tech. Without a reliable, scalable and secure data infrastructure, no pharma company can hope to compete in the coming decade. In the coming years, the challenge will be to expand that infrastructure while keeping data safe from hackers.

 

8.Greater focus on cybersecurity

Pharma companies have been the number one target for elite hackers over recent years. In 2017, Merck lost $300 million in a ransomware attack, while in 2019, Roche discovered that malware was stealing their intellectual property. In 2020, the search for a Covid-19 vaccine was subject to multiple state-sponsored hacks, which emphasized the vulnerability of many pharma companies.

Most companies recognize that this is a vital area, with 48% of pharma executives saying cybersecurity will be the most important technology investment area over the next five years. The main goals of cybersecurity in pharma tech include:

  • Protect intellectual property from falling into the wrong hands
  • Ensure the privacy of personal data, including data from clinical trials
  • Resist criminal attacks, such as ransomware
  • Maintain the integrity of operations and supply chain
  • Preserve the quality of data analytics

Cybersecurity is an evolving threat. While pharma companies are bolstering their defenses, hackers are refining their attacks. The result is a never-ending arms race in which pharma companies must keep investing in data security.

The current wave of digital transformation does at least give you a chance to rethink your approach to cybersecurity from the ground up. It’s a chance to take legacy systems offline and replace them with cloud-based systems that use unbreakable encryption.

9.Pros and cons of remote working

By the end of 2019, almost five million Americans were working from home in some capacity. That figure went skyrocketing in 2020 as states were hit with shelter-in-place orders and employers scrambled to adjust. As restrictions start lifting, it seems like there’s no great desire to go back to the old way of doing things. Remote working is often cheaper for employers, while helping employees to strike a better work-life balance.

However, remote working has only added to the cybersecurity headaches mentioned above. Cloud-based applications allow employees to safely share data off-site, while many enterprise communication tools have high-level encryption. That said, people are the weakest point in any network. Pharma companies may need to consider ways to deal with employees who connect to insecure networks or who leave their laptops unattended in public places.

The pharma sector may also be about to lead a revolution in a new kind of telecommuting: remote work via VR. Virtual Reality technology has a number of applications in pharma. R&D teams can create visual interfaces that they can use for next-gen drug modeling. The manufacturing team can use VR to monitor production facilities in real-time, even if they’re on the other side of the world. Sales teams can connect with clients in VR chat rooms, adding that extra touch to socially-distant relationships.

10.Closer relationships with patients

While pharma companies have been marketing directly to customers for years now, there have been fewer opportunities to build relationships directly with the patient. All of that might be about to change, for several reasons.

First, digital marketing tools allow you to have a two-way conversation with individuals at scale. You can send people personalized messages targeted to their needs, and then gather their feedback via online patient surveys. A growing number of people are using wearable technology with the capacity to gather health information. This data can be immensely valuable for both research and marketing purposes.

Would patients be willing to share their information with a pharma company? According to a study by Accenture, they would, if you ask via a trusted party: patient organizations. In the US, 64% of respondents said that they are happy to share personal details with a patient organization. And an amazing 84% of people said that they think that pharma companies and patient organizations should work closer together.

Looking Forward to 2021

It’s been a bumpy start to the decade, to say the least. A global pandemic like Covid-19 is the biggest challenge that anyone in healthcare could have possibly imagined.

The ripple effects of the virus have also been fascinating. For example, research in The Lancet estimates that over 10,000 deaths may have been prevented by the drop in air pollution during shelter-in-place. Covid-19 has changed the way we work, the way we exercise, the way we think about our bodies, and the way we interact with others.

Life in 2021 will be unrecognizable in some ways. The challenge for pharma companies is to stay agile, respond quickly, and offer support to a changing world. Fortunately, we have access to tech tools that will help us meet this challenge. With quality data and the right pharma tech, the future looks bright.

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