Tony Hogben is the Immersive Studio Lead at Pfizer Digital Omnichannel Companies & Options (OSS). Pfizer Digital Omnichannel Companies & Options (OSS) is on the forefront of reworking how Pfizer connects with sufferers, healthcare suppliers and professionals worldwide. By means of progressive 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 intensive 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 position?
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 through the emergence of Internet 2.0 was really exhilarating. We had been pioneering SAAS options and early cell purposes in an atmosphere the place innovation wasn’t only a buzzword—it was our each day actuality. Each undertaking broke new floor, and the entrepreneurial vitality 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 artistic imaginative and prescient and technical capabilities, drawing on practically twenty years of expertise serving to organisations of all sizes rework digitally.
Constructing the Immersive Studio from the bottom up has been significantly rewarding— creating an inner innovation hub that permits groups throughout the corporate to harness immersive and interactive applied sciences. At the moment, I am a part of a staff spearheading our initiatives to combine AI options throughout a number of departments and use instances, 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 atmosphere the place our work has tangible affect. Right here, the precision, realism, and engagement we create by way of immersive applied sciences instantly influences healthcare skilled training and, in the end, affected person outcomes. This connection between technological innovation and human wellbeing drives me daily.
Medical coaching is present process a shift with AI-driven simulations. How do these AI- powered immersive experiences evaluate to conventional coaching strategies by way of effectiveness and accessibility?
I ought to begin by addressing immersive experiences earlier than exploring how AI is remodeling the panorama.
Immersive coaching experiences basically rework medical training by providing flexibility conventional strategies cannot match. Learners can revisit advanced eventualities from just about wherever, at their very own tempo, and as many instances as wanted. The proof is compelling, data retention charges for immersive studying are vital—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 individuals – this can unlock growth potential and permit content material to be created at scale.
For learner expertise, AI permits dynamic adaptation—adjusting eventualities in real- time primarily based on choices and ability degree, creating genuine challenges that higher mirror medical unpredictability.
On the suggestions entrance, AI offers nuanced evaluation past easy go/fail metrics. It might analyse the learners’ actions, choice sequences, and evaluate efficiency in opposition to 1000’s of earlier classes to supply personalised teaching.
Lastly, AI permits collaborative studying by way of pure language processing and clever avatars that simulate practical affected person and staff interactions.
The accessibility affect is profound—AI-driven immersive experiences may be deployed broadly and cost-effectively, serving to tackle coaching gaps globally. This highly effective mixture of immersive know-how and AI has the potential to democratise entry to high-quality medical coaching, significantly in underserved areas.
*Bonde, Mads & Makransky, Guido & Wandall, Jakob & Larsen, Mette & Morsing Bagger, Mikkel & Jarmer, Hanne & Sommer, Morten. (2014). Bettering biotech training by way of gamified laboratory simulations
Are you able to share insights into how AI-driven medical simulations are being developed at your organization? What are among the greatest challenges in constructing these high- constancy simulations?
We’re within the early levels of integrating AI into our approaches. We’ve 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 would like to hold tempo with the frantic innovation occurring with AI.
At the moment, we’re focusing our AI efforts in three key areas:
- Content material Creation Acceleration: We’re utilizing AI to boost our content material growth pipeline, serving to our medical and tutorial design groups scale manufacturing of evidence-based eventualities, medical variations, and affected person fashions. This enables us to keep up high quality whereas considerably increasing our library of simulations.
- Technical Improvement Acceleration: We’re leveraging AI to streamline our technical growth processes, enabling sooner prototyping, testing, and deployment of latest 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 growing methods to include AI instantly into our simulations to create extra dynamic, responsive studying environments. This consists of personalised suggestions programs and adaptive problem primarily based on learner efficiency patterns.
Whereas progress requires persistence on this area, we’re enthusiastic about how these AI improvements will in the end rework medical coaching and affected person outcomes.
Your 360 diploma expertise, digital laboratory, is an progressive method to coaching healthcare professionals. How does it work, and how much suggestions have you ever obtained from customers to this point?
The 360-degree digital laboratory provides healthcare professionals the expertise of strolling by way of an actual lab atmosphere, interacting with medical gear, 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 reveal greatest practices. We recognised that bodily lab visits contain difficult logistics and scheduling limitations, so we created a digital various accessible 24/7 from wherever on the earth.
Healthcare professionals navigate by way of detailed, interactive simulations that take a look at their data and improve their understanding of laboratory procedures. The platform is designed for a number of units, making certain flexibility in how and the place studying takes place. We have expanded our providing to incorporate digital labs for quite a few medical circumstances and have translated these experiences into many languages to help world training wants.
The suggestions has been overwhelmingly constructive. Customers persistently reward three points:
- Realism: The high-fidelity atmosphere creates an genuine sense of presence in a working laboratory
- Engagement: Interactive parts keep curiosity and focus all through the training expertise
- Flexibility: The flexibility to entry coaching at their comfort and tempo
Most significantly, healthcare professionals report feeling extra assured of their expertise and retaining data 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 obstacles—similar to regulatory considerations, adoption hesitancy, or technical limitations—that have to be overcome?
In terms of implementing new applied sciences in healthcare coaching, the obstacles differ considerably between immersive experiences and AI purposes.
The first challenges with immersive know-how embrace:
- Improvement Prices: Historically, creating high-quality immersive experiences has been costly. Nonetheless, AI is definitely serving to us tackle this by accelerating content material creation and decreasing manufacturing time.
- Accessibility: We guarantee our immersive coaching stays accessible by growing for a number of platforms, as demonstrated with our Digital Lab which works throughout numerous units. This method permits learners to interact no matter their technical setup.
- Adoption Hesitancy: That is maybe our most persistent problem, significantly 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 advanced applied sciences.
For AI integration, we face completely different obstacles:
- Technical Limitations: We’re actively working by way of these by constructing strong platforms and approaches that can function foundations for future developments.
- Regulatory Issues: 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 training. Our method is to develop inner use instances first, creating concrete examples we will use to interact regulatory groups constructively. We recognise we have to help their understanding whereas collaboratively growing acceptable guardrails.
By addressing these obstacles systematically and recognising their distinct traits, we’re creating pathways for accountable innovation that maintains the excessive requirements required in healthcare training.
With AI accelerating at an unprecedented tempo, do you foresee some extent the place AI may tackle a extra energetic position in real-time affected person care, somewhat than simply being a help device?
This steps barely exterior my space of experience, however I believe we will see that AI is already shifting past help roles in healthcare, with examples like AI-assisted diagnostics and real-time surgical procedure steering. Within the subsequent 5 years, I count on AI to tackle a way more energetic position in affected person care, nevertheless it gained’t absolutely change people. As a substitute, 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 may recommend diagnoses or remedy 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 may in the future outperform human professionals in sure duties, how ought to the healthcare business put together for this shift?
With each technological transformation, we see activity displacement somewhat than individuals substitute. The healthcare business must reframe AI not as a substitute for professionals however as a collaborator. It is a easy equation, Human + AI is larger than Human or AI alone.
This shift will likely 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 provides AI a pure benefit, whereas extra advanced 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 method of monolithic options. This iterative method permits clinicians and sufferers to construct belief in AI capabilities over time.
Fairly than resisting change, the healthcare business ought to proactively form how AI is embedded into the healthcare ecosystem, making certain 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 probabilities—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 will deliver that pleasure again to determine significant purposes of their each day work. Backside-up innovation typically produces essentially the most sensible and impactful options.
Many firms wrestle with scaling AI options past pilot initiatives. What methods have you ever used to efficiently implement AI at scale?
For me, efficiently AI scaling any know-how undertaking includes addressing two essential challenges: know-how infrastructure, and consumer adoption.
In healthcare’s closely regulated atmosphere, 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 typically 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 put in writing an efficient immediate creates vital friction for many customers. As a substitute, 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 method prioritises beginning small however constructing with scale in thoughts from day one. Fairly than creating one-off options, we design modular parts that may be prolonged and repurposed throughout a number of use instances. This enables profitable pilots to change into templates for broader implementation.
You imagine AI is ready to remodel healthcare in ways in which had been as soon as thought-about science fiction. What particular developments do you suppose could have essentially the most profound affect over the subsequent 5 years?
As a toddler of the 80s, I keep in mind the Six Million Greenback Man and Bionic Girl TV exhibits from the Nineteen Seventies. These exhibits featured characters bodily augmented by know-how, the true revolution with AI, nonetheless, will likely be cognitive augmentation. This excites me essentially the most.
Over the subsequent 5 years, I imagine a number of different particular developments will basically rework healthcare:
- Administrative Automation: The bureaucratic burden that at present consumes a lot of our healthcare skilled’s time will likely be dramatically lowered. 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 growing efficient therapies will compress from a long time 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 programs will dramatically enhance early detection of circumstances like most cancers, heart problems, and neurological problems by way of sample recognition throughout huge datasets.
- Personalised Therapy: Therapy plans will likely be repeatedly refined primarily based 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 likely be startling. AI growth is like canine years—however with exponential acceleration. We’re going to see what might need taken 50 years of typical analysis and implementation.
These aren’t distant science fiction eventualities—they’re already rising in early varieties, it’s not the long run, it’s now.
