PeakData, the tech start up with the most advanced Artificial Intelligence (AI) in healthcare, today announced important appointments to enter into the next stage of their journey to bring the power of AI to more healthcare organisations.
“To ensure current healthcare clients are getting the most value from our proprietary AI technology and to develop partnerships with new pharma companies, we have now recruited two widely recognized experts who not only understand marketization of medicines but who have significant experience in the healthcare service industry“ said Patrick de Boer, CEO and co-founder of PeakData. “Andy and Sebastian are bringing more than 40 years of pharma experience to PeakData. This combined with their leadership skills will be extremely valuable as we continue to grow the PeakData organisation across Europe and globally.”
Commenting on his new role, Andy said, “I’m thrilled to be joining PeakData at such an exciting growth phase for the organization. The initial response from current and future clients has been very positive, with many decision makers in pharma highlighting a clear need for real time insight at scale that helps to identify ‘digital activators’ and enables micro-segmentation with the personalisation of communication”
Sebastian comments: “My biggest drivers for working in healthcare are to ensure patients get the best treatment available and physicians are empowered to be guiding patients in their choices. Therefore, my goal here is very simple: to ensure healthcare companies can harness the power of AI to be making smart business choices and can ensure physicians are receiving tailored information. The most advanced AI in the healthcare space is enabling companies to optimize their medical and commercial processes, deploying their resources smartly and more efficiently”
Andy joins PeakData as Senior Vice President of Global Client Relations and Managing Director of PeakData Plc effective 1st February 2021. Andy joins PeakData from STEM Healthcare where he held over the last five years several senior leadership roles including President, Global Client Relations. Prior to STEM Healthcare, Andy was at Novartis UK where he held roles of increasing responsibility, including launch leadership for an innovative heart failure medicine and brand leadership responsibility for the severe asthma portfolio.
Sebastian joins PeakData as Senior Vice President of Global Client Relations and Managing Director of PeakData Netherlands B.V. effective 1st April 2021. Sebastian also joins PeakData from STEM Healthcare where he led the STEM business across Central Europe. Prior to STEM Healthcare, Sebastian worked at Bayer for more than 15 years. At Bayer, he held roles at European marketing, UK marketing and in his last role he led the Ophthalmology business in the UK.
Andy and Sebastian will jointly oversee the Global Client Relations team at PeakData. Both will ensure existing healthcare clients are getting the most value and are able to fully integrate the PeakData AI technology into their business processes. In addition – the Global Client Relations Team will identify new partnership opportunities and ensure that more healthcare companies get to leverage the value of PeakData’s proprietary AI engine.
Andy and Sebastian will also be joining the PeakData Leadership Team.
Further appointments will be announced in due course.
To find out more about PeakData, including open positions, please visit us at: https://peakdata.com
The role of AI in the biopharmaceutical sector to date has focused mostly on optimising and accelerating R&D processes and on innovating clinical trials. Those activities belong to the pre-commercialisation stage of bringing a new therapy to market, and have historically absorbed the lion’s share of investment and attention in the industry. But with companies increasingly looking to AI to also support their commercialisation efforts, a new horizon is sliding into view: realising the technology’s potential to revolutionise biopharma’s marketing and sales processes.
Taking an asset to market is the culmination of what is usually a multi-year and multi-billion dollar/euro investment. The granting of a marketing authorisation, however, is not an assurance of success and often many challenges must be addressed to achieve a successful launch. One key factor that is critical to the success of a new medicine is having robust data and insights on which to base your launch strategy and make investment decisions. This could be information about unmet patient needs, treatment paradigms, prescription trends, influence maps in companies’ top accounts, share of scientific communication by segment, KOLs, digital opinion leaders (DOLs), and healthcare providers. In short, access to data is an opportunity for companies to gain competitive advantage before, during, and after product launch, and if there is one characteristic that neatly sums up AI capabilities, it is “expresswaying” access to and interpretation of large volumes of data.
The implication for the industry? Thanks to AI-enabled data analytics, medical affairs, sales, and marketing teams can gain deep commercial insights that not only measure the impact of existing market access and adoption strategies, but also serve as a guide on how to improve them by collecting, interlinking, and pinpointing the most relevant data and messaging approaches for each target stakeholder group. In particular, by gaining a deeper understanding of their KOLs and relationship networks in real time, medical affairs teams can craft highly tailored scientific communications, and by harnessing the power and speed of AI in the pre-launch phase, improve their understanding of a new therapy area at scale very quickly.
One of the most intuitive applications of AI in drug commercialisation is enabling high-precision profiling of HCPs, so that marketers can design customised outreach strategies instead of relying on a traditional one-size-fits-almost-all approach. AI technologies make this possible by micro-segmenting key stakeholder groups not only across therapy area, publishing output, or visibility – the traditional approach taken in audience segmentation. They also do so according to size of individual physicians’ professional networks and the degree centrality they occupy in them, communications preferences, availability, and location. Further, AI can search beyond companies’ existing customer data sets and unearth new cohorts of practitioners who may be open to considering novel treatments for some of their patients. The results can be applied to optimise engagement strategies, connect with would-be partners via their preferred communication channels, and ultimately increase market adoption rates.
In the same way that AI technologies can tap into public online databases and extract KOL and HCP-level data at a fraction of the time it would take a person to do it, they can garner patient-level data. For example, an AI algorithm trained to process natural language in the medical domain can harness data found in public forums or social media channels where patients share personal experiences of using a particular therapy or a drug. Those comments can then be cross-linked with physician-level observations shared in a similar social context, yielding multi-perspective insights from openly shared real-world evidence (RWE). Having such data enriches pharma companies’ understanding and monitoring of product performance across indication, region, physician specialty, type of patient (e.g. GP practice, hospital, specialty clinic), or type of payer (public vs. private). Lastly, AI-enabled social listening can also be leveraged to detect patterns in prescribing behaviour and to assess prevailing public sentiment towards new or existing medications, which are essential tools for running brand diagnostics.
On the regulatory and compliance front, AI can accelerate drug commercialisation by reducing the time and human resources that are invested into compliance review, allowing the latter to be shifted towards more demanding cognitive tasks that cannot be automated. AI-powered analyses can also help leaders decide how to deploy sales teams across a geographic region or therapy area for greatest return on investment, using insights from the micro-segmentation and social listening applications described above to determine what type of content and communications channel would be most impactful for each.
Last but not least, data-driven AI technologies can support drug commercialisation in the post-marketing or pharmacovigilance stage by compiling publicly shared data on undesirable side effects in real time. This can help companies conduct causality assessment on an ongoing basis and react faster to minimise damage to both patients’ health and the health of their own brand image.
Adoption challenges in Europe
Despite the competitive edge promised by embedding AI and machine learning-powered technologies into pharma´s commercial operations, the EU biopharma industry has been slow to adopt such technologies , according to a report by IQVIA published in 2018. Although the survey cited dates back to 2018 and company readiness to embrace AI has likely improved since then, it is an “open secret” in the industry that in comparison to the U.S. and some Asian countries, Europe is not moving as fast as it should and could.
How PeakData can help
PeakData’s Healthscape software can support organisations that are ready to deploy AI for drug commercialisation. It comprises a set of tools that perform real-time web wide market intelligence based on publicly available, decision-shaping conversations about drug uses and indications, real-world outcomes, and patient and provider-generated insights across social media, peer-reviewed publications, preprint repositories, press releases, conference agendas, and other formal and informal sources. This comprehensive search is complemented by rigorous and nuanced analysis of the findings, according to client-defined variables and characteristics, to obtain a panoramic view of all the open data and social signals generated around a drug that is about to go to market or is already being commercialised. As an added value, Healthscape’s capabilities are governed by a clear strategy for sourcing the data such complex AI searches require.
If you are interested in learning more about Healthscape and how it can make AI a reality in your company´s marketing and sales strategies, we invite you to schedule a demo.
Commercial teams nowadays are being asked to deliver sales pitches while swimming in an ocean of product, customer, and performance data. This is nowhere more challenging than in the highly regulated pharmaceutical industry, where promoting new treatments must be calibrated so as to grab the attention of busy clinicians with little spare time and convert it into business without resorting to hard selling, all while reaching the right stakeholders whose influence can multiply the effect of a sale. Deploying a Big Data-driven market research approach can be a powerful tool in orchestrating such a tightrope act.
Today, a dependence on labour-intensive manual research on the one hand and an overwhelming amount of raw data on the other can surpass the analytical capacity of even the most effective sales rep, leading to missed opportunities to leverage untapped insights.
This is where a Big Data-driven approach can help. A well-designed research methodology can breathe new life into lead generation by identifying with laser-like precision those clinicians that are most open to receiving sales pitches in a particular disease area. To generate such insights, it can automate the tracking of some clinician activities that tend to go unnoticed, the number of times a drug or therapeutic area is mentioned in a speech or presentation, or pre-print publishing in medRxiv and other non-peer reviewed repositories. The value of monitoring these activities is that it pinpoints in real time, sometimes serendipitously, the latest medical topics that circulate in the medical community before they make it to top journals. Having such customized knowledge at their fingertips can be extremely valuable for reps and marketers alike, as it provides them with a blueprint for personalizing their communication with individual clinicians. This increases the odds of securing precious “attention share” and, ultimately, converting attention into sales.
Another way Big Data can aid brand teams in refining customer value propositions is by providing insights into KOL feedback and scientific discussion around a given drug or disease area. Such insights, derived mostly from social listening via Twitter, Reddit, and other online platforms, allow pharma teams to filter marketing pitches on individual KOL criteria as expressed in more subtle and informal ways. Insights may include conversations about competitor products and activities that can help reps anticipate and “disarm” unhelpful comparisons, and they may even be geolocated for even higher customization.
To apply this level of granularity to their B2B and B2C operations, pharma companies need to invest in the necessary tools and capabilities. Opting for an external platform that collects, consolidates, and analyses such data can be a powerful, cost-effective solution.
However companies choose to go about it, the important thing is to let go of the “analogue mindset” and pivot to more data-rich, nuanced business intelligence tactics. The stakes of not doing so are simply too high: insufficiently targeted marketing, sales pitch overload for clinicians, burnout for sales team members, and reduced market share for the firm. Some organisations are fully aware of the benefits of leveraging Big Data in their marketing strategies, yet are failing in the implementation.
Healthscape, a software platform that transforms pharma-relevant data into actionable insights, has answers to these questions. By simplifying the process from data collection to analysis across multiple categories – clinical usage, social listening, competitor activity, events, and publications – it removes a major logistical challenge for marketing and sales professionals, as they no longer have to extract and triage this information manually. Its suite of customizable tools and algorithms slices and dices the data any which way that makes decision-making most efficient and coherent. In a nutshell, it helps commercial teams develop a more sophisticated understanding of HCPs and empowers them to focus on the highest-hanging fruit: building KOL loyalty and long-term sales potential.
So talk to us and let us show you a demo of how Healthscape can supercharge your business. We are sure it will delight you.
Over the past few years, physicians and other KOLs have been increasingly mindful of the time they spend with pharma sales representatives. Many of them have been reducing this time investment in favour of engaging with more scientifically knowledgeable MSL’s (Medical Science Liaisons) that can double as educators and help them stay abreast of new therapeutic products and developments. This shift in attitudes has thrust medical affairs teams into the spotlight and is transforming them into one of the pharma industry´s most prized assets.
The rise to stardom of the MA function corresponds with an ever-growing attention being paid by HCPs and payors to patient outcomes and other aspects of value-based healthcare that MA professionals are uniquely qualified to address. At the same time, they are highly attuned to the constantly evolving regulatory environment and its implications, especially as concerns transparency and compliance. This understanding of the regulatory landscape, combined with their deep product knowledge and sensitivity to the demands of value-based pricing and contracting, empower them to have meaningful exchanges with HCP’s in ways no other business function can. Yet, in many pharma companies this powerhouse of ingenuity is held back, and medical science liaison (MSL) staff are still regarded as mere product advisers.
Indeed, research conducted by Bain´s Healthcare practice as far back as 2017 highlighted this organisational blindspot when it found that one of the main reasons 50% of new drug launches fail is that companies do not adapt fast enough to new information channels used by physicians. The report foresaw three upgraded roles for MA teams that address this and other challenges: leading the communication of scientific evidence, feeding stakeholder insights into all stages of the R&D process and not just during post-launch assessment, and overseeing initiatives to produce outcomes research and real-world evidence.
The rationale for concentrating this triple leadership role into the hands of MA teams is that they can authoritatively explain how a new product or indication fits into clinical practice at the same time as give evidence on how it impacts patient outcomes – the latter being the holy grail of any biopharmaceutical offering. With patients themselves having become important stakeholders in healthcare, conveying patient-reported outcomes or unmet medical need to physicians in the language of real-world evidence both helps advance the practice of medicine and builds trust in the industry as a good-faith actor. And with more than four-fifths of physicians both in Europe and in the U.S. citing RWE as their key criterion for prescribing drugs, according to the Bain findings, it is clear why professionals versed in outcomes research are the right messenger.
Further, as clinicians begin using new treatments and sharing their observed impact on patients, MSLs are uniquely positioned to bring those insights back to the lab to drive improvements to next-generation drug development. Thus, they can effectively become the glue that binds together the expertise of physicians, the needs of patients, and the drive for innovation in the industry.
But while recognizing the vast potential of MA teams is long overdue, laying all these responsibilities on their shoulders without additional support would be unrealistic. The creation of value for pharma companies, KOLs, and patients they can realise requires the untapping of deep, sometimes simultaneous, insights from all healthcare stakeholders and painting them together into a coherent knowledge map. Finding these insights in turn depends on the mining and exploration of data spread across a multitude of official and unofficial web sources and social media platforms. It is a Herculean task that, to be completed efficiently, exceeds the capacity of the human brain if it tries to “go it alone.”
That´s why we created Healthscape, an AI-powered data mining and analytics platform designed to lend a virtual hand to your MA team and be its partner in navigating the stormy waters of data. It can uncover and transform into practical information all types of structured and unstructured data, including those related to RWE, KOL insights, social listening, and even business intelligence. So send us an email or give us a call and let us show you how Healthscape can equip your company with all it needs to keep an edge on the competition.
Influencer ecosystems are continually evolving in response to changing consumer preferences and the pharmaceutical sector is no exception. On one hand, patients and their doctors are looking beyond traditional Key Opinion Leaders (KOLs) for guidance on therapies and treatments and want to hear from alternative sources, such as Patient Opinion Leaders (POLs), whose feedback resonates on both personal and real-world evidence level. On the other hand, as a growing number of people seek information online, they discover a parallel universe of Digital Opinion Leaders (DOLs), who tend to have a large followership and are more approachable. We wrote about this expanding universe of Opinion Leaders (OLs) in a previous blog.
Despite these shifts, many pharma companies cling to the idea that KOLs represent the best, safest, most authentic marketing partners. Yet as audiences are increasingly more diverse, better informed, and often skeptical of authority figures who speak only to their “filter bubble” of similarly credentialed physicians, KOLs are really just one of several types of sources healthcare professionals look to for advice and information.
Not only that, but the term “KOL” itself has begun to lose its luster. As far back as 2015, 62% of medical professionals and 56% of pharmaceutical executives believed that it should be replaced, according to a survey of nearly 400 respondents from both Europe and the U.S. On the physician side, many respondents felt that it is often used too loosely or attached to people who do not warrant that title or the trustworthiness implied by it. On the pharma side, many others signaled that their companies were phasing out use of the term because of its unflattering connotations and it being seen as “marketing speak.” It is reasonable to assume that in the five years since that survey was conducted, the “KOL” terminology has hardly gained back much support.
In the context of this less-than-enthusiastic adoption of the “KOL” concept, it is obvious why alternatives such as DOLs and POLs have been gaining currency. But what makes the most novel among them – Connected Opinion Leaders (COLs) – stand apart from the rest and what is their value to pharma companies?
Although COLs´ profiles seem similar to others, their unique feature is that they bring together the best of the KOL, DOL, and POL worlds. They are not only digitally savvy, relatable, and with an active presence across multiple content channels, but are also sought-after experts, published authors, and conference speakers. And it is precisely their panoramic view of the industry from both a professional and a communications perspective make them a strategic partner to pharma marketers who want to deliver sleek messaging to an engaged professional network.
To build a relationship with COLs, the industry must expand the prism through which it searches for them. Instead of relying only on traditional metrics, such as impact factor of journals they publish in or conferences they present at, it should seek to glean insights on factors such as who else is in their networks or what publicly communicated research projects they participate in. Pharma marketers should then triage those traditional metrics with social stats such as the frequency of their online activity, number of followers, geographic reach, likes, and reposts/retweets, to name a few. Once identified, to then engage them in a sustainable, authentic partnership, pharma marketers should consider offering them membership on advisory boards, consultancies, or content creation on blogs or proprietary websites, where their expertise, communication and social skills can truly shine. At PeakData, our software platform HealthScape™ can help your company develop an effective strategy for identifying COLs with the highest potential and relevancy for your business. For example, our algorithms and comparison tools let you sift through data on healthcare professionals labeled according to multiple features, select the ones that meet your essential criteria in terms of therapeutic area or publications, and then triage the results against relevant social metrics to understand each person´s reach and digital footprint. Give us a chance to show you a new, smarter way of choosing who you entrust with your marketing message – we are sure our solution will surprise, inspire, and delight you.