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 reworking how Pfizer connects with sufferers, healthcare suppliers and professionals worldwide. By modern 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 group 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 area, 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 actually exhilarating. We have been pioneering SAAS options and early cellular functions in an setting 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 rapidly realised I wanted a brand new problem that might 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 significantly rewarding— creating an inner innovation hub that allows groups throughout the corporate to harness immersive and interactive applied sciences. At present, I am a part of a group 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 setting the place our work has tangible affect. Right here, the precision, realism, and engagement we create by immersive applied sciences immediately 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 reworking the panorama.
Immersive coaching experiences basically remodel medical schooling by providing flexibility conventional strategies cannot match. Learners can revisit advanced situations from nearly anyplace, at their very own tempo, and as many occasions as wanted. The proof is compelling, information 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 – it will unlock growth potential and permit content material to be created at scale.
For learner expertise, AI permits dynamic adaptation—adjusting situations in real- time primarily based on selections and ability stage, creating genuine challenges that higher mirror scientific unpredictability.
On the suggestions entrance, AI gives nuanced evaluation past easy go/fail metrics. It might probably analyse the learners’ actions, resolution sequences, and evaluate efficiency towards 1000’s of earlier classes to supply personalised teaching.
Lastly, AI permits collaborative studying by pure language processing and clever avatars that simulate practical affected person and group 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, significantly in underserved areas.
*Bonde, Mads & Makransky, Guido & Wandall, Jakob & Larsen, Mette & Morsing Bagger, Mikkel & Jarmer, Hanne & Sommer, Morten. (2014). Enhancing biotech schooling by 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 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 need to innovate rapidly and our obligation to proceed rigorously—we would like to preserve tempo with the frantic innovation occurring with AI.
At present, 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 situations, scientific 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 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 creating methods to include AI immediately into our simulations to create extra dynamic, responsive studying environments. This contains personalised suggestions methods 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 finally remodel medical coaching and affected person outcomes.
Your 360 diploma expertise, digital laboratory, is an modern strategy 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 an actual lab setting, interacting with medical gear, training procedures, and fixing real-world challenges in a totally immersive digital area.
The digital lab was designed to enhance in-person excursions of working laboratories that reveal finest practices. We recognised that bodily lab visits contain difficult logistics and scheduling limitations, so we created a digital various accessible 24/7 from anyplace on the planet.
Healthcare professionals navigate by detailed, interactive simulations that take a look at their information 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 circumstances and have translated these experiences into many languages to help international schooling wants.
The suggestions has been overwhelmingly constructive. Customers constantly reward three elements:
- Realism: The high-fidelity setting 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 information retention interprets immediately to raised affected person care in real-world settings.
AI and immersive tech could make coaching extra accessible, however do you see any boundaries—similar to regulatory considerations, adoption hesitancy, or technical limitations—that must be overcome?
On the subject of implementing new applied sciences in healthcare coaching, the boundaries 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 decreasing 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 varied gadgets. This strategy permits learners to have interaction 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 totally different obstacles:
- Technical Limitations: We’re actively working by these by constructing strong platforms and approaches that can 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 will use to have interaction regulatory groups constructively. We recognise we have to help their understanding whereas collaboratively creating acceptable guardrails.
By addressing these boundaries 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 a degree the place AI might tackle a extra lively position in real-time affected person care, somewhat than simply being a help software?
This steps barely outdoors my space of experience, however I believe we will see that AI is already transferring past help roles in healthcare, with examples like AI-assisted diagnostics and real-time surgical procedure steerage. Within the subsequent 5 years, I anticipate AI to tackle a way more lively position in affected person care, but it surely gained’t totally substitute 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 may recommend diagnoses or therapy plans, the ultimate resolution 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 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 folks alternative. The healthcare business 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 shall 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 scientific reasoning will stay human-led for the foreseeable future.
We have to begin with small, focused duties that ship rapid 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.
Moderately than resisting change, the healthcare business 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 will deliver that pleasure again to establish significant functions of their day by day work. Backside-up innovation usually produces probably the most sensible and impactful options.
Many firms 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 includes addressing two vital challenges: know-how infrastructure, and person adoption.
In healthcare’s closely regulated setting, establishing strong technical foundations is important earlier than scaling any AI initiative. We’d like 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 and needing to write 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. Moderately 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 ready to remodel healthcare in ways in which have been as soon as thought of science fiction. What particular developments do you assume could have probably 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 Girl TV reveals from the Nineteen Seventies. These reveals featured characters bodily augmented by know-how, the actual revolution with AI, nonetheless, shall be cognitive augmentation. This excites me probably 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 the moment consumes a lot of our healthcare skilled’s time shall be dramatically decreased. 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 constructions—fixing in days what beforehand took years of laboratory work.
- Precision Diagnostics at Scale: AI methods will dramatically enhance early detection of circumstances like most cancers, heart problems, and neurological issues by sample recognition throughout huge datasets.
- Personalised Therapy: Therapy plans shall be constantly refined primarily based on particular person affected person information, adjusting in real-time to maximise effectiveness and sufferers’ engagement in their very own care.
The tempo of those adjustments shall be startling. AI growth 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 varieties, it’s not the long run, it’s now.