Tony Hogben is the Immersive Studio Lead at Pfizer Digital Omnichannel Providers & Options (OSS). Pfizer Digital Omnichannel Providers & Options (OSS) is on the forefront of remodeling how Pfizer connects with sufferers, healthcare suppliers and professionals worldwide. By means of revolutionary digital methods, cutting-edge know-how, and data-driven insights, OSS powers seamless, personalised, and impactful experiences. By integrating superior analytics, automation, and AI-driven options, the staff enhances engagement, optimises communication, and drives significant connections throughout all digital touchpoints.
You’ve had an in depth profession in digital innovation and immersive applied sciences. What first sparked your curiosity on this subject, and the way did your journey lead you to your present function?
My path has been considerably unconventional. After finishing a level in ‘New Media’ on the flip of the century—when digital was nonetheless discovering its footing—I established and ran my very own digital company. Working in the course of the emergence of Net 2.0 was really exhilarating. We had been pioneering SAAS options and early cellular functions in an surroundings the place innovation wasn’t only a buzzword—it was our day by day actuality. Each mission broke new floor, and the entrepreneurial power was infectious.
After efficiently promoting my enterprise simply earlier than the pandemic, I initially loved the downtime, however shortly realised I wanted a brand new problem that may leverage my experience. Becoming a member of Pfizer Digital has allowed me to mix each my inventive imaginative and prescient and technical capabilities, drawing on almost 20 years of expertise serving to organisations of all sizes remodel digitally.
Constructing the Immersive Studio from the bottom up has been notably rewarding— creating an inner innovation hub that permits groups throughout the corporate to harness immersive and interactive applied sciences. At present, I am a part of a staff spearheading our initiatives to combine AI options throughout a number of departments and use circumstances, serving to groups reimagine their workflows and capabilities.
What’s been most fulfilling about transitioning to healthcare is making use of my ardour for the intersection of know-how and human expertise in an surroundings the place our work has tangible affect. Right here, the precision, realism, and engagement we create via immersive applied sciences instantly influences healthcare skilled schooling and, finally, affected person outcomes. This connection between technological innovation and human wellbeing drives me on daily basis.
Medical coaching is present process a shift with AI-driven simulations. How do these AI- powered immersive experiences evaluate to conventional coaching strategies when it comes to effectiveness and accessibility?
I ought to begin by addressing immersive experiences earlier than exploring how AI is remodeling the panorama.
Immersive coaching experiences basically remodel medical schooling by providing flexibility conventional strategies cannot match. Learners can revisit complicated situations from nearly wherever, at their very own tempo, and as many occasions as wanted. The proof is compelling, data retention charges for immersive studying are important—as much as 76% higher than conventional coaching strategies*
AI is now revolutionising these immersive experiences in 4 essential methods:
In content material creation, AI is democratising the event of high-fidelity simulations. What as soon as required groups of specialized builders and months of labor can now be accomplished sooner and by far fewer folks – this may unlock improvement potential and permit content material to be created at scale.
For learner expertise, AI allows dynamic adaptation—adjusting situations in real- time based mostly on selections and ability stage, creating genuine challenges that higher mirror medical unpredictability.
On the suggestions entrance, AI offers nuanced evaluation past easy go/fail metrics. It will probably analyse the learners’ actions, choice sequences, and evaluate efficiency in opposition to 1000’s of earlier classes to supply personalised teaching.
Lastly, AI allows collaborative studying via pure language processing and clever avatars that simulate lifelike affected person and staff interactions.
The accessibility affect is profound—AI-driven immersive experiences will be deployed extensively and cost-effectively, serving to handle coaching gaps globally. This highly effective mixture of immersive know-how and AI has the potential to democratise entry to high-quality medical coaching, notably in underserved areas.
*Bonde, Mads & Makransky, Guido & Wandall, Jakob & Larsen, Mette & Morsing Bagger, Mikkel & Jarmer, Hanne & Sommer, Morten. (2014). Bettering biotech schooling via gamified laboratory simulations
Are you able to share insights into how AI-driven medical simulations are being developed at your organization? What are a few of the greatest challenges in constructing these high- constancy simulations?
We’re within the early phases of integrating AI into our approaches. We’ve got a transparent imaginative and prescient of the place we’re heading, however the closely regulated healthcare area we work in necessitates methodical implementation and rigorous validation. This creates a stress between our want to innovate shortly and our obligation to proceed fastidiously—we might like to maintain tempo with the frantic innovation taking place with AI.
At present, we’re focusing our AI efforts in three key areas:
- Content material Creation Acceleration: We’re utilizing AI to reinforce our content material improvement pipeline, serving to our medical and educational design groups scale manufacturing of evidence-based situations, medical variations, and affected person fashions. This enables us to take care of high quality whereas considerably increasing our library of simulations.
- Technical Improvement Acceleration: We’re leveraging AI to streamline our technical improvement processes, enabling sooner prototyping, testing, and deployment of recent simulation options and capabilities. That is serving to us overcome useful resource constraints and speed up our innovation cycle.
- Learner-Adaptive Experiences: In parallel, we’re creating methods to include AI instantly into our simulations to create extra dynamic, responsive studying environments. This contains personalised suggestions techniques and adaptive problem based mostly on learner efficiency patterns.
Whereas progress requires endurance on this area, we’re enthusiastic about how these AI improvements will finally remodel medical coaching and affected person outcomes.
Your 360 diploma expertise, digital laboratory, is an revolutionary strategy to coaching healthcare professionals. How does it work, and how much suggestions have you ever obtained from customers up to now?
The 360-degree digital laboratory offers healthcare professionals the expertise of strolling via an actual lab surroundings, interacting with medical tools, practising procedures, and fixing real-world challenges in a totally immersive digital area.
The digital lab was designed to enrich in-person excursions of working laboratories that show greatest practices. We recognised that bodily lab visits contain difficult logistics and scheduling limitations, so we created a digital different accessible 24/7 from wherever on this planet.
Healthcare professionals navigate via detailed, interactive simulations that check their data and improve their understanding of laboratory procedures. The platform is designed for a number of gadgets, guaranteeing flexibility in how and the place studying takes place. We have expanded our providing to incorporate digital labs for quite a few medical situations and have translated these experiences into many languages to assist world schooling wants.
The suggestions has been overwhelmingly optimistic. Customers persistently reward three points:
- Realism: The high-fidelity surroundings creates an genuine sense of presence in a working laboratory
- Engagement: Interactive parts preserve curiosity and focus all through the training expertise
- Flexibility: The power to entry coaching at their comfort and tempo
Most significantly, healthcare professionals report feeling extra assured of their abilities and retaining info higher than with conventional coaching strategies. This improved data retention interprets instantly to raised affected person care in real-world settings.
AI and immersive tech could make coaching extra accessible, however do you see any limitations—reminiscent of regulatory considerations, adoption hesitancy, or technical limitations—that have to be overcome?
In the case of implementing new applied sciences in healthcare coaching, the limitations differ considerably between immersive experiences and AI functions.
The first challenges with immersive know-how embody:
- Improvement Prices: Historically, creating high-quality immersive experiences has been costly. Nevertheless, AI is definitely serving to us handle this by accelerating content material creation and lowering manufacturing time.
- Accessibility: We guarantee our immersive coaching stays accessible by creating for a number of platforms, as demonstrated with our Digital Lab which works throughout numerous gadgets. This strategy permits learners to have interaction no matter their technical setup.
- Adoption Hesitancy: That is maybe our most persistent problem, notably amongst skilled healthcare professionals. Our technique is incremental publicity—beginning with acquainted codecs like our Digital Lab that introduce spatial studying ideas with out requiring a steep studying curve. This builds consolation with immersive ideas earlier than advancing to extra complicated applied sciences.
For AI integration, we face totally different obstacles:
- Technical Limitations: We’re actively working via these by constructing strong platforms and approaches that may function foundations for future developments.
- Regulatory Considerations: This represents our most important problem. Regulatory our bodies have legitimate questions in regards to the accuracy and validity of AI- generated content material in healthcare schooling. Our strategy is to develop inner use circumstances first, creating concrete examples we are able to use to have interaction regulatory groups constructively. We recognise we have to assist their understanding whereas collaboratively creating applicable guardrails.
By addressing these limitations systematically and recognising their distinct traits, we’re creating pathways for accountable innovation that maintains the excessive requirements required in healthcare schooling.
With AI accelerating at an unprecedented tempo, do you foresee some extent the place AI might tackle a extra energetic function in real-time affected person care, somewhat than simply being a assist software?
This steps barely exterior my space of experience, however I believe we are able to see that AI is already transferring past assist roles in healthcare, with examples like AI-assisted diagnostics and real-time surgical procedure steering. Within the subsequent 5 years, I anticipate AI to tackle a way more energetic function in affected person care, however it received’t totally exchange people. As an alternative, AI will work alongside healthcare professionals in a “human-in-the-loop” framework, providing help with out taking full management. This shift raises moral considerations round belief and accountability—whereas AI would possibly counsel diagnoses or therapy plans, the ultimate choice will nonetheless be made by people to make sure affected person security. AI will improve decision- making, however human judgment will stay important.
In a world the place AI-generated medical insights might at some point outperform human professionals in sure duties, how ought to the healthcare trade put together for this shift?
With each technological transformation, we see process displacement somewhat than folks alternative. The healthcare trade must reframe AI not as a alternative for professionals however as a collaborator. It is a easy equation, Human + AI is bigger than Human or AI alone.
This shift will probably be gradual and task-specific—possible starting in areas like image-based diagnostics, pathology screening, and predictive analytics for affected person deterioration. These are areas the place sample recognition at scale offers AI a pure benefit, whereas extra complicated medical reasoning will stay human-led for the foreseeable future.
We have to begin with small, focused duties that ship instant worth somewhat than the same old all-or-nothing strategy of monolithic options. This iterative strategy permits clinicians and sufferers to construct belief in AI capabilities over time.
Relatively than resisting change, the healthcare trade ought to proactively form how AI is embedded into the healthcare ecosystem, guaranteeing it enhances somewhat than diminishes the human parts that stay central to therapeutic.
Finally, step one any organisation ought to take is democratising AI publicity. Give your workers private challenges to open their eyes to the chances—have them create a picture, write an e-mail, or construct a presentation utilizing AI instruments. As soon as they expertise the facility firsthand, they’re going to carry that pleasure again to establish significant functions of their day by day work. Backside-up innovation usually produces essentially the most sensible and impactful options.
Many corporations wrestle with scaling AI options past pilot tasks. What methods have you ever used to efficiently implement AI at scale?
For me, efficiently AI scaling any know-how mission entails addressing two crucial challenges: know-how infrastructure, and consumer adoption.
In healthcare’s closely regulated surroundings, establishing strong technical foundations is important earlier than scaling any AI initiative. We want safe, compliant infrastructure that balances innovation with affected person security necessities.
With new know-how, adoption usually turns into the best barrier to scale. We have discovered that making AI as invisible as attainable is essential to widespread adoption. For instance, being confronted with a clean display screen and needing to jot down an efficient immediate creates important friction for many customers. As an alternative, we’re designing options the place customers can merely click on pre-configured buttons or use acquainted workflows that leverage AI behind the scenes.
Our strategy prioritises beginning small however constructing with scale in thoughts from day one. Relatively than creating one-off options, we design modular elements that may be prolonged and repurposed throughout a number of use circumstances. This enables profitable pilots to grow to be templates for broader implementation.
You consider AI is about to rework healthcare in ways in which had been as soon as thought-about science fiction. What particular developments do you assume could have essentially the most profound affect over the subsequent 5 years?
As a toddler of the 80s, I bear in mind the Six Million Greenback Man and Bionic Lady TV reveals from the Seventies. These reveals featured characters bodily augmented by know-how, the true revolution with AI, nevertheless, will probably be cognitive augmentation. This excites me essentially the most.
Over the subsequent 5 years, I consider a number of different particular developments will basically remodel healthcare:
- Administrative Automation: The bureaucratic burden that at present consumes a lot of our healthcare skilled’s time will probably be dramatically diminished. This is not nearly effectivity—it is about placing the care again into healthcare by redirecting human consideration to affected person interactions.
- Drug Discovery Acceleration: The timeline from figuring out therapeutic targets to creating efficient therapies will compress from many years to years and even months. AlphaFold, created and open sourced by Google’s DeepMind, has already revolutionised our understanding of protein buildings—fixing in days what beforehand took years of laboratory work.
- Precision Diagnostics at Scale: AI techniques will dramatically enhance early detection of situations like most cancers, heart problems, and neurological problems via sample recognition throughout huge datasets.
- Personalised Therapy: Therapy plans will probably be repeatedly refined based mostly on particular person affected person knowledge, adjusting in real-time to maximise effectiveness and sufferers’ engagement in their very own care.
The tempo of those modifications will probably be startling. AI improvement is like canine years—however with exponential acceleration. We’re going to see what might need taken 50 years of standard analysis and implementation.
These aren’t distant science fiction situations—they’re already rising in early kinds, it’s not the longer term, it’s now.
