Improving the data flow of information between stakeholders will make pharma more agile
The global pharmaceutical industry today is worth $1.2 trillion, projected to rise by 40 percent in just three years' time[1]. To realize this potential, greater agility is required. Organizations are now investing in collaboration technologies to help breaking out of silos and borders and share data throughout the entire pharma value chain to exploit new opportunities.
Communication and collaboration are the essence of the pharmaceutical industry. It not only involves exploring how to share and analyze information with external partners, but also enabling the flow of data through across the entire medical ecosystem.
“We see ourselves shifting from the mindset of a traditional pharma company to [one] more inherently agile, typical of a tech company,” says Badhri Srinivasan, head of global development operations for Novartis, illustrating the goal of the modern pharma company.
However, only 20 percent of pharma firms are considered digitally mature – that is, those that have specialist digital leaders within the organization that drive positive change – according to a 2018 report by MIT Sloan[2].
Many organizations recognize the value of collaboration – between humans first, but also human-to-machines-and-things communication. As they undertake digital transformation, they're exploring new ways of collaborating using new networks, tools and work processes. Some companies are taking their cue from transformation that organizations in other vertical sectors are making, incorporating 'lessons learned' along the way. Meanwhile, on the human side, companies are also adapting to the cultural change required for a new digital mindset among employees.
In the next few years, the flexibility to collaborate as well as the agility to respond to the market will be key. Firstly, real-time feedback from medical trials can shorten the length and cost of trials, while also allowing more accurate analysis of results.
Next, on the production line, machines with sensors can collaborate with humans to deliver critical manufacturing data that warns of potential issues, providing instant information that helps troubleshooting.
Finally, during distribution, systems can alert pharma organizations to environmental conditions that could cause damage to drug quality.
All roads lead to more outward-facing collaboration between pharma companies, to move on from a history of closed work groups, across medical trial and care facilities, insurance companies, doctors, research scientists, along with machines and devices themselves.
Interestingly, about 80 percent of interviewees in a recent Deloitte survey[3] said that they sought to work with pharma organizations as true partners, not just sales organizations, and "to form a close relationship and align supply and demand needs more seamlessly." This shows a demand which is now being met by advanced communications networks, devices, data collection and analytics.
It takes an average of 12 years and costs about $2 billion to bring a drug to market, and yet most clinical trials are unsuccessful[4]. Investment in trials has increased in recent years, but results are no more accurate and generic drugs are pressuring margins and placing a squeeze on profitability.
One answer to this conundrum lies in the aggregation, analysis and sharing of data collected from clinical trials. Much of this data is created in real time, creating a huge amount of information. In addition, the volume and proliferation of different formats of data produced from electronic medical records, health insurance information, genomics, social media and wearables, is increasing; enabling more accurate risk assessments for clinical trials.
But if pharma can capture and share all of this information with other stakeholders, it promises to create efficiencies that will help organizations streamline some of their internal processes as well as tackle new markets, such as the requirement for personalized medicines. It will also drive a greater level of automation throughout the internal research and production lifecycle, while sharing it effectively with external organizations and stakeholders for better decision making.
The advent of Real-World Evidence (RWE) - which provides clinical data direct from patients, monitoring devices and diagnostic systems - can reduce the timeframe and expense of trials and offer results that speed time-to-manufacture and time-to-market.
In a recent survey, Deloitte asked pharma organizations how advanced they were in taking advantage of RWE. 90 percent of respondents said they had invested and were working on establishing RWE capabilities for use across the entire product lifecycle. But only 45 percent had capabilities that were mature enough to do that[5].
The various interactions required with all the stakeholders of the value chain, using different and sometimes incompatible systems, can make collaboration difficult inside the organization as well as outside. The key here is to invest in flexible, open solutions that foster sharing opportunities and are future-proofed against what tomorrow's requirements will be.
5 factors to consider in pharma collaboration