Quantum: The Regulatory Frontier That Will Catch Us Off Guard

Yesterday, I met Sabrina Maniscalco, CEO of Algorithmiq, at the Italian Tech Forum in Zurich. They develop quantum algorithms for life sciences, including applications in cancer therapy. Despite having taken two courses in quantum physics at university and working extensively with AI/ML medical devices, I found myself needing to educate myself from scratch on what quantum computing means for our field.

What I discovered was both inspiring and unsettling: we're standing at the edge of a paradigm shift in medical technology, and regulatory science isn't even looking in that direction yet.

What Is Quantum Computing and Why Does It Matter?

Classical computers operate using bits, each either 0 or 1. Quantum computers use qubits that can exist in multiple states simultaneously through superposition. Qubits can also be entangled, meaning their states are interconnected regardless of distance. This allows quantum computers to process vast possibilities in parallel in ways classical computers simply cannot replicate.

For medtech, this isn't academic curiosity—it's transformative capability. Classical computers struggle to simulate even simple molecules beyond a certain size. A molecule with just 30 atoms has more quantum states than a classical computer can practically track.

Quantum computers can model:

• Drug-molecule interactions at atomic precision

• Protein folding and three-dimensional structures

• Tumor microenvironments at cellular and molecular levels

• Personalized treatment responses based on genetic profiles

The AI-Quantum Hybrid Approach

During our conversation, Sabrina explained: "AI is only as good as the data it's trained on. With quantum computing, we can generate vast amounts of physically accurate data and then train AI on it. Imagine the possibilities from simulating the behavior of ALL atoms in our body."

This is Algorithmiq's innovation: combining quantum computing with AI to address one of AI's fundamental limitations—the need for massive training data.

For many biological phenomena, we simply don't have enough experimental data. It's too expensive, too dangerous, or physically impossible to measure. Quantum computers can generate synthetic training datasets that are physically accurate—based on quantum mechanics—but impossible to obtain experimentally.

Sabrina mentioned that quantum computing capabilities are now available on the cloud, with enterprise access in the million-dollar range annually. For specific computational problems, quantum computers can be more efficient than traditional supercomputers.

Algorithmiq has already announced partnerships with Microsoft (December 2024) and Quantum Circuits (February 2025) to accelerate drug discovery.

A Concrete Example: Photodynamic Cancer Therapy

One particularly compelling application demonstrates quantum computing's real-world impact: photodynamic therapy (PDT) for cancer.

PDT uses special molecules called photosensitizers that are activated by light to produce therapeutic effects. The benefits are significant:

• No long-term side effects

• Less invasive than surgery

• Outpatient procedure

• Precisely targeted

• Can be repeated at the same site (unlike radiation)

• 5-10 times less costly than other cancer treatments

The challenge lies in designing these photosensitizer molecules. It requires understanding tiny energy gaps between electronic states—differences that dictate how molecules behave when exposed to light. Classical quantum chemistry algorithms struggle to calculate these energy gaps with the necessary accuracy.

Using IQM's Emerald quantum processing unit and Algorithmiq's advanced error mitigation techniques, the team achieved a 100x improvement in precision compared to results from other quantum hardware providers. This work, part of the Wellcome Leap Q4Bio Challenge, is establishing an end-to-end quantum-centric drug discovery pipeline for light-activated anti-cancer drugs.

They're focusing on the BODIPY class of compounds—next-generation photosensitizers. With quantum computing, simulating their energy landscape becomes possible with unprecedented accuracy, paving the way for better-targeted therapies developed faster and more cost-effectively.

This is happening now.

Closing Health Data Gaps

We also discussed possibilities that particularly resonate with my work in femtech: using quantum computing to simulate complex biological systems like women's physiology to close health data gaps that are difficult or impossible to obtain experimentally.

Women's health research has historically been underfunded. Menstrual cycles, pregnancy, menopause—these introduce biological complexity that makes clinical trials more expensive and results harder to interpret. What if quantum simulation could help bridge these gaps by modeling hormonal interactions and reproductive system responses with atomic-level precision?

The Regulatory Challenges Ahead

Here's the uncomfortable truth: none of medtech's regulations or guidances currently contemplate quantum-AI hybrid diagnostics or therapeutics.

Challenge 1: The Validation Paradox

How do you validate quantum-generated data when you can't reproduce it classically?

The FDA's recent draft guidance on AI/ML-enabled device software (January 2025) requires manufacturers to disclose synthetic data provenance, describe algorithms used to generate it, and demonstrate it preserves clinical correlations. These are sensible requirements for classically-generated synthetic data.

But they break down when the "algorithm" is a quantum computer simulating physics that classical systems fundamentally cannot reproduce. How do you verify quantum-generated molecular data "preserves clinical correlations" when there's no classical ground truth? The entire point of quantum computing is simulating phenomena classical computers cannot.

Challenge 2: Black Box Squared

AI is already a "black box"—how do we maintain our ability to explain and reproduce the operating principles when we layer quantum computing on top?

Explainability is already a regulatory challenge. The EU MDR Article 61 and FDA guidance emphasize transparency in clinical decision-making. But AI models, particularly deep learning, are notoriously opaque.

Add quantum computing—inherently probabilistic, extraordinarily sensitive to environmental interference—and we're layering one form of opacity on another. Yet regulatory frameworks require that medical devices be explainable, reproducible, and transparent.

The FDA's three-pillar framework for Software as a Medical Device asks:

1. Is there a valid clinical association between device output and clinical condition?

2. Does the software correctly process input data?

3. Does use of the output achieve the intended purpose?

For quantum-AI systems, how do you analytically validate "correctness" when there's no classical benchmark?

Challenge 3: Cybersecurity and Q-Day

Quantum computers will eventually break current encryption methods—a threat called "Q-Day." This poses serious risks:

• Adversaries can collect encrypted medical data today and decrypt it later

• Medical devices relying on current cryptographic protocols will be compromised

NIST announced its fifth quantum-safe algorithm in March 2025, but adoption in medical devices has been slow. Medical device manufacturers should implement quantum-resistant encryption immediately.

What Regulatory Frameworks Currently Exist?

The closest we have are two recent FDA guidances:

FDA Guidance on Real-World Evidence (December 2025) emphasizes that data must be relevant and reliable, with a fit-for-purpose approach. This potentially opens a pathway: quantum-generated synthetic data could be acceptable if manufacturers demonstrate it's the most appropriate method for answering specific clinical questions.

FDA Guidance on AI/ML-Enabled Device Software (Draft, January 2025) addresses data management, synthetic data requirements, performance validation—but all assuming classical computational paradigms.

Neither contemplates quantum-generated training data, validation when classical reproduction is impossible, or uncertainty quantification for quantum probabilistic outputs.

The EU AI Act, MDR/IVDR, and ISO standards similarly don't address quantum computing.

Why This Matters Now

Waiting until quantum devices reach the clinic or reach their "ChatGPT moment" means we'll be reactive instead of proactive, again.

We've seen this pattern with AI. By the time ChatGPT brought AI to mainstream awareness, the technology had been developing for decades. Regulators scrambled to catch up.

But AI builds on classical computing principles we already understood. Quantum computing is fundamentally different. The learning curve is steeper, the validation challenges more complex.

If we wait until a quantum-enhanced diagnostic applies for FDA clearance before starting these conversations, we'll be years behind.

So, what needs to happen?

Regulatory agencies may:

• Introduce quantum-aware terminology in guidance documents

• Establish working groups bringing together quantum scientists, device developers, and regulatory professionals

• Develop validation frameworks specifically for quantum-generated synthetic data

• Issue guidance on quantum-resistant cybersecurity for medical devices

Industry may:

• Engage early with regulators through pre-submission meetings

• Document quantum approaches in detail

• Build quantum literacy within regulatory and quality teams

• Implement post-quantum cryptography now

Thank you to Sabrina Maniscalco for the thought-provoking conversation, and to Camera di Commercio Italiana a Zurigo for creating the space where these insights happen.

References

• Algorithmiq's Photodynamic Therapy Demonstration

• IQM Quantum Breakthrough in Cancer Therapy

• FDA Software as a Medical Device (SaMD): Clinical Evaluation

• FDA guidance: “Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices”

• FDA guidance: “Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence/Machine Learning (AI/ML)-Enabled Device Software Functions”

• FDA guidance: "Software as a Medical Device (SAMD): Clinical Evaluation"

  Methodology Note: This article is based on my original LinkedIn post, reflecting my professional experiences and personal perspectives. Claude AI assisted in elaborating the post into a broader article by integrating personal notes, literature research, fact-checking and deeper insights on the topic. All analysis and regulatory perspectives are my own, and all content has been reviewed by me for accuracy.

Beyond the EU-US paradigm

The recent speech delivered by Canada's Prime Minister at the World Economic Forum prompted me to reconsider my approach to regulatory strategy. Without delving into politics, the address highlighted the extent to which the western world has become US-centric and reliant on American frameworks—a reality that extends fully to the medical technology sector.

This led me to reflect on my own professional practice:

• Most of my analysis focuses on comparative regulatory matters between the EU and US.

• Most of my medtech clients prioritize EU and US market entry first, and that is what I help them achieve.

• Most of my knowledge accumulated over 14 years in healthtech has been built on the default EU-US paradigm.

However, I am far from blind to the strong signals of change emerging on a global level.

Major medtech corporations are beginning to pursue UAE market entry first, given that average regulatory approval timelines are 30%-50% shorter than in the US and EU. Many emerging economies maintain low regulatory barriers for standalone Software as a Medical Device (SaMD) in digital health—large markets such as Mexico and Nigeria only introduced such requirements in 2023 and 2025, respectively. Meanwhile, Canada, Australia, and the UK are taking bold steps to boost health innovation, attract technology companies, and facilitate regulatory compliance.

As former Bank of England Governor Mark Carney stated in his remarks:

"In a world of great power rivalry, the countries in between have a choice: to compete with each other for favour or to combine to create a third path with impact."

"The question is not whether to adapt—we must. The question is whether we adapt by simply building higher walls or whether we can do something more ambitious. The former is easy and ruinous; the latter is difficult and necessary."

This brings me to an important question for the medtech regulatory community.

Beyond the US-EU 'old order', which regulatory focus would you find most valuable for future analysis and guidance?

1. Anglosphere: Canada, South Africa, Australia, New Zealand

2. "BRIC" + Japan: Brazil, Russia, India, China, and Japan

3. Middle East: UAE, Saudi Arabia, Israel

4. Emerging Markets: Africa, ASEAN, Latin America
   
   I invite you to share your perspective in the poll here

Crans-Montana, a compliance perspective

Regulation is often seen as pain in the neck… until it isn't. A national tragedy takes place in Switzerland on NYE, and we ask ourselves why didn’t this underground bar have compliant emergency exits? Why wasn’t it inspected in more than 5 years? How could a combustible soundproofing material be permitted and line the whole ceiling? How could staff pull off such a deadly stunt (regularly!) with zero awareness about fire risk? Why the heck were the victims-to-be filming instead of fleeing??

And in particular, how could ALL these hazards manifest simultaneously??

I am horrified by the incident in Crans-Montana (news article). It should never have been. It lights up the painful memory of the Grenfell tower fire in 2017, which had shocked me deeply as I was living in London back then.

We all assume and expect to be protected by regulation. We all assume and expect compliant and responsible behaviour of others. The reality is that if things go south, we are on our own to face the consequences. We all have a responsibility to do our bit, whether it’s fire safety or health.

Being alert to risks, and raising the awareness of others too. Informing yourself and doing your best at least, not ignoring. Holding others accountable by asking questions or reporting unsafe practices. Raising your voice to policy-makers if something isn't enough.

I hope my work does a bit on all these things, within the realm of healthtech, of course, not fire regulation.

As a result, Switzerland now banned the use of pyrotechnics in indoor spaces and is investigating not only the bar owners but the municipality, that did not inspect the bar ONCE in 5 years. The sale of any flammable soundproofing materials is also under scrutiny.

Could this bring into 2026 a bigger wave of respect for regulation and compliance? Am I hopelessly wishful?

Today in Switzerland is a national day of mourning for the 40 victims, mostly teenagers. It breaks my heart to think of what’s left of the 116 injured.

I pray for them and for something like this to not be allowed to happen again - by regulators, by business owners, by fellow citizens, by luck (that's a factor too..🍀), by us all doing our little responsible part in society.

(Image rights: https://www.bbc.com/news/articles/c9dvyyjyj18o)

MDR/IVDR proposal for simplication

12 hours ago the European Commission published THE MOST AWAITED AND CRUCIAL DEVELOPMENT IN A DECADE: its proposal for simplification of the MDR and IVDR. 👏

Alert: it is still only a proposal, albeit official, which has been submitted to the European Parliament and the Council, but will need to go through the ordinary legislative procedure to become binding Union law.

From a first diagonal read, what struck my attention:

🎉 More room for Class I devices, incl software (THANK YOU!)
🎉 Simplified interaction with AI Act
🎉 Codified instruments for open dialogue on classification and access to expert panels
🎉 Easier "equivalence" concept including use of synthetic data,
🎉 Lower NB fee structure for SMEs
🎉 Extended reporting timelines and validity of certificates
🎉 Reduced scope of surveillance audits and conformity assessment
🎉 Built-in flexibility for public health emergencies, breakthrough/orphan devices (i.e. life-threatening, rare, untreated diseases), supply-chain disruptions

Interestingly, but unsurprisingly, it proposes additional requirements for cybersecurity conformity and reporting (beyond what qualifies as medically "serious").

I will share more details of how this would impact specifically medical device startups especially in digital health and femtech.

While it is still ONLY A PROPOSAL, it is sign that EU is listening and actively working to "make [the current rules] easier, faster and more effective and further promote competitiveness, innovation and a high-level of patient safety in this key sector"

We're excited to follow the development of the legislative decision-making process and wait eagerly for the change of an era this (or its variants that will result) will bring to the European medtech sector!

Link to proposal

What can we learn from… a progressive Notified Body?

Medtech governance in Europe is highly decentralised, with product certifications also being "outsourced" to private entities (i.e. Notified Bodies). This would be complicated enough if classic Notified Bodies didn't also bring their own enormous challenges to the table: lack of availability, lack of new tech competence, lack of transparency and communication.. Companies feel they have no control over their destiny.

So what's Scarlet doing differently as a Notified Body:
1️⃣ Focus on one subject matter (digital devices only) to ensure top and uptodate competence
2️⃣ Fit the conformity assessment process around the applicant and their timelines
3️⃣ Engage transparently and pragmatically about expectations in pre-sub Structured Dialogues
4️⃣ Scale resources flexibly with externals

and, my favourite,

5️⃣ Train their trusted consultants in an independent manner in order to increase the chance of high quality submissions and enable more effective reviews.

Which other NBs do this? None that I'm aware. But please share if you know any good practices you've experienced.

Therefore, I'm particularly enthusiastic to have been part of this special training session last Friday! Not only with a like-minded NB, but among a group of 18 like-minded regulatory experts ❤️

New times and new tech need a new approach - a mantra of Edge Compliance. I hope other and new NBs will take example.

Note: I'm not affiliated but believe the initiative deserves genuine praise and broadcasting.

Thank you Dan Levy and Sandy Wright at Scarlet - also for the photo credit. Stellar job!

Regulation without borders

Starting two new client projects this week, one on food supplements in France and one on in-vitro diagnostics in Germany, both in womens health!

Very few medtech consultants would feel comfortable touching other verticals (even from MDR to IVDR). But my career started like that when, honestly, I didn't have a choice! Now it's what I enjoy the most, and what I built my agency around.

The hard competences boil down to a few common traits, irrespective of sectors, regs and countries:
➡️ Regulatory definition / classification
➡️ Manufacturing requirements
➡️ Claims and label compliance
➡️ Responsible Person / Entity role
➡️ Notification / Submission procedures
➡️ Review interaction
➡️ Launch and Distribution
➡️ Post-market reporting

After all, it's all about health accountability, and humans have really one way of expecting it - the rest is often noise.

Personally, I find it super fun to come across these analogies, transfer learnings from one area to another and even anticipate cross-sector currents. Excited to get going!

Review timelines for FDA 510k clearance

How long does it take from FDA submission to clearance?
Let's look at the recent data.

The 510k database can be exported and analysed. Format is not humanly readable but makes a fun ChatGPT exercise.

Here is the result of me playing with the database from devices cleared last months (Aug and Sep 2025).

❗ The normal distribution appears to peak around 90 days, the legal obligation for FDA to respond to submissions. Around 30% of submissions were cleared within that timeframe.
❗ Nice peak at 30 days - but don't be too wishful! These are expedited reviews, e.g. changes to existing 510ks or based on prior agreements or expected updates.
❗ Less exciting peak around 270 days, i.e. 9 months. Most submissions receive an Additional Information request, which gives manufacturers 180 days to respond and restarts the clock for FDA after that (further 90 days).

Lesson here?
If you're planning a 510k, a realistic estimate for clearance is nothing less than 6 months. This is what applied to 2/3s of the 400+ applications cleared most recently.

Good quality submissions and preliminary discussions with FDA on the fundamental topics can help prevent Additional Information requests and thus increase the chances of receiving clearance within 90 days.

Does your experience confirm this too?

I will dig more into this database in the coming posts with more insights.

US Gov shutdown: impact on FDA operations

After Republican and Democratic politicians could not agree to pass a bill funding government services, on 1st October the US federal government has shut down. Though not unusual (almost every administration had at least one, lasting from a couple of days to a top 35 days), they create immediate uncertainty for largely Congress-funded agencies such as the FDA.

FDA announced that, based on its contingency plan, it will limit its ops to “mission critical activities including responding to public health emergencies, supporting high-risk food and medical product recalls, and conducting essential surveillance of medical devices and other medical products”.

So in practice, until the end of the shutdown:

🔴 No new submissions accepted (510k, DeNovo) nor payments thereof,
🟡 Ongoing reviews will continue but may suffer delays beyond the mandatory timeframes and potential unresponsiveness,
🔴 Annual fees will not be processed (MDUFA user registration), though due in October for Fiscal Year 2026 - see my previous post on increased fees,
🟢 Medical device recalls and safety surveillance will continue,
🟡 Inspections largely on hold except if “for cause”.

Tough news if you are on the brink of submitting or awaiting a decision. But history tells us these don't last long, so be ready to move fast once the shutdown lifts.

Is it cake? New bordeline guideline rundown

Here the regulatory version of “IS IT CAKE??” 🍰 - if you know the show! Featuring the European Commission’s updated guidance on borderline products published this month.

As someone whose specialty is borderline products and who loves RA developments on the edge, I spent hours digesting its 24 examples of what is or isn’t a medical device - as opposed to drugs, cosmetics, IVD, personal protective equipment (PPE), biocides,..

Frankly, I found half of the examples straightforward, and the other half.. I either struggle to understand the reasoning, disagree or find it inconsistent. Here the main reasons:

INTENDED USE vs MODE OF ACTION, WHO WINS?
MDR defines and classifies medical devices based on the former, while this guidance mostly hedges on the latter. When conflicts arise, this guidance gives priority to the mode of action. There are two, in my opinion, conflicting examples with devices that claim prevention of disease: an STI prevention app and medical examination table covers (i.e. paper roll). The first is not MD, despite processing medical records, using algorithms to assess risk, alerting peers regarding their potential for infection - because “no action on data other than communication”. The second is MD, regardless of its make - because “acts as a mechanical barrier”.

ANYTHING BUT Class I, EVER..
The myth of Class I devices continues. Only one example from here comes out as Class I MD: a rescue bag for patient transport - because "aims to support and protect, [..] avoids worsening of health". Arguably, PPE and Product for Emergency Rescue regulations could be sufficient, so what does Class I MD status really add here? On the other hand, why couldn’t some other low risk examples be Class I (e.g. STI app above, medical calculator for recurrent math)?

It's a continuous learning process for all, and access to practical guidance of this type is very helpful for the health sector as a whole - actually something that FDA does way better (writing style and formal consistency in this manual is quite disappointing).

If we held a geeky RA pub quiz on these examples, how would RA professionals, national authorities and notified bodies score? That would be interesting.

At Swiss Medtech 2025

Swiss Medtech events never disappoint!
Key learnings from attending yesterdays session in sunny Bern (inside a stunning casino!):

1️⃣ US tariffs and lower FDA capacity are discouraging EU/CH startups from going US-first, but there are clever best-practices to work around them.

2️⃣ EU's gap between numbers in MDR applications and certifications is widening in unsustainable ways due to a poor EU-wide governance model for medtech, and how this needs fixing ASAP.

3️⃣ Switzerland is working out creative legal basis to be an attractive alternative (e.g. to fast-track FDA medical devices and to modernise its regulatory framework faster than the EU can)

4️⃣ Emerging markets (e.g. Saudi Arabia) get devices to market 6 months faster than traditional markets, meaning their patients get better outcomes, HCPs get better education, and the healthcare system innovates exponentially faster.

Grateful to Bernhard Bichsel and Sandra Item from ISS AG, Integrated Scientific Services, Daniel Delfosse, Eva von Mühlenen, LL.M., from Sidley Austin LLP, Glenda C. Marsh from Johnson & Johnson MedTech for putting together such an inspiring and informative afternoon!

EU AI Act deployment

Since August 2nd the EU AI Act is in force. But is it?
In practice: not much today, but the clock has started. If your device includes an AI component or uses AI to support decisions it’s time to take a closer look.

For high-risk systems, including many AI-based medical devices, there’s a 36-month transition to comply, i.e. phased implementation. However, some provisions apply earlier (e.g. banned uses of AI, codes of conduct).

Here’s what I see across medtech:
1. Confusion around scope and classification, e.g. AI as a tool for CSV or as part of the intended use?
2. Assumptions that MDR = AI Act compliance, thus reactive attitude to QMS updates upon NB feedback rather than in a proactive manner
3. Teams don't know how to resource it.

Good thing is that I also see a booming AI-related offering from QARA consultants and training providers which can help if you’re stuck on any of the above points. Cool examples (among many others):

• AI-first QARA frameworks and training e.g. Johner Institut GmbH https://lnkd.in/dBSuFfie,
• AI agents for compliance-checking and even FDA review outcome prediction such as Lexim AI or Acorn Compliance,
• GenAI embedded in eQMS tools such as Formwork from OpenRegulatory or Matrix One

What would help your team implementing the AI Act? Curious to hear your challenges and to help you with the right support.

Steep rise in FDA fees for 2025-2026

Alert 🫰 Steep rise in FDA fees from this October:

+19% Annual establishment registration fee from $9,280 to $11,423 (this is the one you pay every year for keeping the right to place a device on the market)

+7% Application fees, e.g. 510k submission from $24,335 to $26,067 (this is the one-off fee for review of a product submission file)

Bad news for early stage medtech businesses and SMEs, in particular since no "small business discount" nor waivers apply on the establishment fee at first registration.

Note, small businesses may qualify for waiver on the establishment fee (2nd year on) and a reduced application fee (e.g. 510k for $6,517 instead of $26,067, new fees) under the SBD programme. Conditions are based on gross sales and justification of "financial hardship", rather than on company size. Worth looking into.

See latest MDUFA fees on the FDA website at this link.

Quality whistleblower - hero vs martyr

How do you make yourself heard when you MUST raise the redflag over design quality, production compliance, clinical safety?

It's an incredibly difficult position to be in, whether you're acting from inside a company or as an external reviewer, stakes are high and office politics (if not even higher politics), budget concerns, along with own self-limiting beliefs, come into play giving you many reasons why you shouldn't follow your gut. Maybe I'm wrong, maybe it's all well. Or maybe it isn't?

I've been in this position before a couple of times as PRRC. It's dire, sleepless nights, conflict escalation. Escalate it to whom? If the technicians or QA's voice is not heard, and your voice as PRRC is not heard, then you hope external parties such as lawyers, consultants, CROs, reviewers will be more effective gate keepers, but then they aren't. They may overlook things or also have their own interests at play. Then who is left to protect the patient? Who is going to stand up and stop the chain of events before it's too late?

The story of Frances Oldham Kelsey, FDA medical reviewer in the 60s who refused to approve Thalidomide is a great example, and similarities can be seen in other preventable disasters such as Titan's OceanGate, Boeing's 737max MCAS software, or Chernobyl to name the most famous. All had a long chain of brave flag raisers in a culture that shut them down..

Culture is key and of utmost importance in medtech. Accountability, feedback and psychological safety create space for risks to be raised and taken seriously at any stage of a project. So called "Type 1 decisions" in business, i.e. non-reversable (launch or not launch?) need true raw information, not just the glossed version that the manager is willing to lend an ear to.

A culture that integrates Quality as their biggest asset and strategic partner will value anyone who raises issues, mistakes, inefficiencies, with a view of preventing not only harm but also resources and reputational risks.

I'm so deeply passionate about driving such cultural shifts and help teams innovate in the most progressive, forward-looking and responsible ways.