Welcome to the Design Thinking for Deep Tech course

I’m Dr Chloe Sharp and will be your instructor. It’s great to see you here.

I am a big believer in Design Thinking. I’ve used Design Thinking for many years, applying it through research and business leadership approaches. It’s an amazing problem-solving tool and is also a process that you can follow.

This course is designed for founders of EngBio startups and Deep Tech technical founders to maximise the benefits of Design Thinking in their business.

I have spent most of my career bridging the gap between brilliant technology and real-world human problems. I wrote the book on this (Make Products That Matter), and I am here to guide you through applying these principles to your ventures.

Design thinking has a high ROI as it encourages innovation, reduces costs and increases revenue through better products. It can deliver an ROI of 85% or more (Forrester, 2018), reduce the time to market and be applied to a whole organisation, and not just a few roles.

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The Deep Tech Entrepreneurship Challenge

You've spent years mastering your science. You've probably published papers, defended your thesis, and proven yourself as a researcher. You can engineer metabolic pathways, design novel materials, or develop breakthrough diagnostics. Your technical capability is exceptional.

But building a company requires a completely different skillset and language.

You need to understand customer needs (not just technical problems). Design business models (not just experiments). Navigate regulatory pathways and manufacturing scale-up. Communicate with investors who don't understand your science. Make strategic decisions under uncertainty. Build commercial operations. Here is a startup glossary in case you need one.

Most technical training doesn't prepare you for this.

PhDs teach you to be rigorous, thorough, and cautious. To hedge your claims, document everything, and focus on the mechanism. But entrepreneurship demands different skills: comfort with ambiguity, bias toward action, customer empathy, strategic thinking, and the ability to communicate complex science simply.

Brilliant innovations can and do fail unnecessarily.

Not because the science is bad. Not because markets don't exist. But because technically brilliant founders:

Build solutions without deeply understanding customer needs
Over-engineer products that don't create sufficient value
Underestimate regulatory and manufacturing challenges
Can't articulate their value proposition to non-technical stakeholders
Treat entrepreneurship as a linear technical project rather than an iterative learning journey

This course bridges that gap.

It teaches you the methodology that successful deep tech companies use to navigate from laboratory insight to commercial impact. Design thinking is a structured approach to understanding problems, developing solutions, and building businesses that puts human needs at the centre.

Unlike digital product approaches that emphasise 'fail fast,' this course teaches capital-efficient learning to front-loading cheap validation (customer interviews, concept tests) before expensive experiments (pilots, manufacturing). Every milestone is a strategic de-risking step, not just rapid iteration.

This course teaches venture design, not just product design. You're developing technology and simultaneously designing the complete business system: value proposition, business model, regulatory pathway, manufacturing approach, and go-to-market strategy, all working together.

What Makes This Course Different

1. Built Specifically for Deep Tech

This isn't generic startup advice adapted for science. It's designed from the ground up for the unique challenges of engineering biology and deep tech ventures:

Long development timelines - You can't pivot weekly like a software startup. The course teaches strategic planning appropriate for 2-5 years of technical validation journeys.
Regulatory complexity - Your product needs Medicines and Healthcare products Regulatory Agency (MHRA) approval, Food Standards Agency (FSA) authorisation. The course integrates regulatory thinking from day one.
Manufacturing challenges - You can't deploy code; you need bioreactors, supply chains, and quality systems. The course covers scale-up systematically.
High capital requirements - You need millions before generating revenue. The course teaches how to de-risk progressively to unlock funding.
Technical uncertainty - Your technology might not work at scale. The course teaches systematic proof-of-concept and validation.
B2B complexity - You're selling to sophisticated corporate buyers with long procurement cycles. The course teaches enterprise customer development.

Every framework, example, and tool is tailored to deep tech realities.

3. Translations from Digital to Deep Tech

Here are the four key shifts that make this approach work for engineering biology ventures and different from its digital applications:

From "Minimum Viable Product" to "Proof of Concept"

Digital startups build MVPs where minimal feature sets can launch and test with users quickly. But in deep tech, you often can't (or shouldn't) ship a minimal product:

Your technology isn't proven yet
Regulations prohibit untested products
Manufacturing on a small scale is impossible
Customers won't adopt unproven solutions

Instead, I show you the Design-Build-Test-Learning (DBTL) cycle and we’ll cover the importance of the Proof of Concept.

From "User-Centred" to "Ecosystem-Centred"

Digital design thinking focuses intensely on the end user. Deep tech requires a broader vision, as your technology may be part of a bigger ecosystem. Your "users" are embedded in complex systems:

Regulators who must approve your product
Manufacturers who must produce it
Supply chain partners who must deliver materials
Key opinion leaders who influence adoption
Internal champions who navigate procurement
Payers who must authorise spending

This course teaches ecosystem thinking: Understanding and designing for this entire constellation of stakeholders, not just end users.

From "Fail Fast" to "Capital-Efficient Learning"

Silicon Valley's "fail fast, iterate often" mantra doesn't work when:

Each experiment costs £50K+ and takes 6 months
Failure means burning investor capital and team runway
You can't easily pivot when you've invested years in regulatory approval
Your technology requires a long-term commitment to validate

This course teaches capital-efficient learning. This means front-loading the cheapest forms of validation (customer interviews, desk research, concept tests) before committing to expensive prototypes and pilots. Every experiment is a strategic investment with clear learning objectives. You learn fast, but you don't fail expensively.

From "Product Design" to "Venture Design"

Digital products can succeed with great UX alone. Deep tech products can have a perfect user experience and still fail if:

The business model doesn't support the cost structure
Manufacturing can't scale economically
The regulatory pathway takes longer than the runway
IP position isn't defensible
Key partnerships don't materialise

I take you from product design thinking to venture design thinking. You're designing a product and a complete business system. Technology, business model, regulatory strategy, manufacturing approach, team structure, and go-to-market all must work together.

These differences make design thinking authentic to deep tech, not just superficially applied.

2. Follows the Double Diamond Framework

The course is structured around the Double Diamond design methodology, typically used by grant funders. It’s been adapted for deep tech:

Discover (Divergent): Cast a wide net to understand the landscape, talk to many stakeholders, and explore multiple problem spaces. Don't commit too early.

Define (Convergent): Synthesise learnings, identify the highest-impact opportunity, and focus your efforts. Make strategic choices.
Develop (Divergent): Generate multiple solution approaches, prototype and test, learn through experimentation. Embrace technical uncertainty.
Deliver (Convergent): Prove what works, eliminate what doesn't, scale systematically. Build commercial operations.

This isn't a linear process—you'll move through multiple double diamonds at different scales throughout your company's journey. But it provides a reliable structure for navigating uncertainty.

4. Combines Customer-Centric and Technology-Centric Thinking

Many startup courses emphasise "customer development" to the exclusion of technical validation. But deep tech requires both:

Customer-Centric:

What problems do customers actually have?
What solutions do they currently use?
What would they value enough to pay for?
How do we validate this with real customers?

Technology-Centric:

What's technically feasible?
What proof points do we need?
How do we systematically de-risk?
What's the path to scale?

This course teaches you to dance between these perspectives—validating customer need while proving technical feasibility, understanding market pull while demonstrating technology push.

5. Practical and Action-Oriented

Every lesson includes:

Frameworks you can use immediately - Canvas templates, interview guides, decision matrices

Real examples from deep tech - Case studies from synthetic biology, materials, diagnostics, food tech

Exercises to apply learnings - Customer interviews, business model canvases, pitch practices

Templates and tools - Ready-to-use documents for your own venture

I believe action is important and having the tools to put what you learn into practice. You'll leave each lesson with specific actions to take and tools to use.

6. Uses a Case Study to Bring Theory to Life

Throughout the course, you'll follow GlutenAway. This is a fictional but realistic engineering biology company developing enzymes for food allergen removal. You'll see how they:

Discovered and validated customer needs
Built and tested their business model
Planned their technical pathway
Proved their concept
Ran customer pilots
Scaled to commercial production
Adapted and evolved over time

This continuity helps you see how concepts connect and how real companies navigate the full journey.

Who This Course Is For?

Engineering Biology PhD Students and Postdocs with Early Stage Startups

If you're a scientist or engineer considering commercialising your research, this course is designed for you. Specifically:

PhD students exploring entrepreneurship alongside (or instead of) academic careers
Postdocs considering startup founding as next career step
Research scientists at universities or institutes with potentially commercialisable technology
Technical co-founders who need to understand the commercial and strategic aspects of building a company

You might be researching:

Synthetic biology and metabolic engineering
Biomanufacturing and fermentation
Enzyme engineering and protein design
Diagnostics and biosensors
Biomaterials and biopolymers
Therapeutics and drug discovery
Agricultural biotechnology
Environmental biotechnology

The principles apply broadly across engineering biology and adjacent deep tech fields.

Early-Stage Deep Tech Technical Founders

If you've already started your deep tech venture but feel uncertain about commercial strategy, customer validation, or business model design, this course will help you:

Systematise your customer discovery
Validate (or pivot) your business model
Plan your technical and commercial pathway
Communicate more effectively with stakeholders
Build processes that scale

What You Need to Succeed

Technical foundation: You understand your scientific domain and have technical credibility.

Openness to learn: You're willing to embrace methodologies from outside science (business, design, social science). I know you’re a technical genius in your field. Being open to learning and getting feedback outside of your field and comfort zone will help you succeed in the long run.

Curiosity about customers: You're genuinely interested in understanding human needs, not just solving technical puzzles.

Bias toward action: You're willing to run experiments, talk to strangers, test assumptions—not just read, think about it and plan.

Time commitment: Each lesson takes 2-3 hours to complete, plus time for exercises and interviews. Budget 30-40 hours total for the full course.

Course Structure

Course Overview

A Course Overview and Key Learning Objectives

What is Design Thinking?

Lesson 1: Why is Design Thinking Needed in Deep Tech?
Lesson 2: An Overview of Design Thinking: A Way to De-risk Deep Tech
Lesson 3: Taking Design Thinking a Step Further: Tools and Mindsets

DISCOVER + DEFINE: Understanding the ecosystem

Lesson 1: Understanding Your Market - Learning from What Exists
Lesson 2: The Thinking Before Doing (Part 1)
Lesson 3: Having the Conversations (Part 2)
Lesson 4: From Data to Direction: Turning Research into Insights
Lesson 5: Defining Your Business Model and Value Proposition Early On

DEVELOP: From ideas to Proof of Concept

Lesson 1: Getting Creative - Generating Solutions Worth Building
Lesson 2: From Many Ideas to The Right Experiment - Prioritising and Testing Solutions
Lesson 3: Proof of Concept - Proving Your Technology Works

DELIVER: Piloting your technology

Lesson 1: From Lab to Customer - Preparing and Running Your First Pilots
Lesson 2: From Pilots to Production - Scaling Up Systematically
Lesson 3: Translating Science for Commercial Impact
Lesson 4: Continuous Design Thinking

Resource and Wrap-Up

Wrap-Up
Resources

What You’ll Learn From This Course

Throughout this course, I hope that you develop a wide range of skills, which will complement your technical skills.

Skills You’ll Develop

Customer Development:

Conduct discovery interviews that reveal true needs (not just polite interest)
Identify early adopters and design partners
Validate willingness to pay before building
Structure pilots that prove value
Convert early customers into advocates

Strategic Thinking:

Plan multi-year technical pathways with clear milestones
Make strategic choices about focus vs. expansion
Balance technical risk with market risk
Think in terms of systems, not just products
Navigate regulatory and manufacturing complexity

Business Model Design:

Understand your value proposition from the customer perspective
Design revenue models appropriate for deep tech
Build business models that account for long timelines and high capital needs
Identify key partnerships and resources
Test business model assumptions systematically

Communication:

Translate technical concepts for non-expert audiences
Craft compelling narratives (not just data dumps)
Pitch effectively to investors
Present to customers in their language
Build confidence without arrogance

Technical Validation:

Design rigorous proof-of-concept experiments
Document for IP and regulatory purposes
Prove technology works in real-world conditions
De-risk systematically through staged validation
Know when you've proven enough vs. need more data

Operational Capability:

Build quality systems appropriate for your stage
Understand regulatory pathways for your product
Plan manufacturing scale-up
Establish support infrastructure
Create processes that scale beyond founders

Frameworks and Tools You'll Master

Design Thinking Frameworks:

The Double Diamond (Discover-Define-Develop-Deliver)
Customer journey mapping
Persona development
Jobs-to-be-Done framework

Business Strategy Tools:

Value Proposition Canvas
Business Model Canvas
DBTL Cycle
Five-stream de-risking framework (T-S-R-C-IP)

Validation Methodologies:

Customer discovery interview techniques
Concept testing approaches
Pilot program design
Success metrics and KPIs

Communication Frameworks:

Problem-Solution-Impact narrative structure
Elevator pitch formula
Investor pitch deck structure
Layered explanation technique

Operational Frameworks:

Gate-based development planning
QMS implementation roadmap
Three-stage scaling (Systemise-Stress Test-Scale)
Continuous learning systems

What This Course Is and Is Not

This course is:

A methodology for navigating uncertainty - Systematic approach to learning, deciding, and executing
Customer-centric strategic thinking - How to build ventures that create real value for real customers
Practical and actionable - Tools, templates, and frameworks you use immediately
Based on real deep tech patterns - Examples, case studies, and wisdom from actual ventures
Foundation for entrepreneurial journey - Core capabilities you'll use throughout your company's life

This course is not:

A guarantee of success - Entrepreneurship is risky. Many factors affect outcomes. This gives you better tools, not certainty.
A substitute for doing the work - You'll learn frameworks, but you must apply them. That means hundreds of customer conversations, experiments, and iterations.
A technical course - We won't teach you synthetic biology, fermentation, or analytical methods. We assume you have technical competency and will use the information we have about technical aspects as guidance.
Legal or financial advice - We introduce IP and funding concepts, but are not lawyers or financial advisors. Get professional help for critical decisions.
Sector-specific - We teach general principles applicable across deep tech, not detailed regulatory pathways for specific sectors (though we provide examples).
A shortcut - Deep tech takes years. This helps you navigate those years more effectively, not skip them.
Complete and comprehensive - No single course covers everything. You'll need to learn financial modelling, legal structures, HR, and fundraising details elsewhere.

Let’s Get Going!

Building a deep tech company is one of the most difficult things you can do. It will take years and will require enormous effort and patience. It will test your technical skills, business acumen, communication ability, resilience, and determination. Many will fail. But some will succeed spectacularly.

The successful ones won't necessarily have the most innovative technology. They'll be those who:

Understand customer needs deeply
Make strategic decisions wisely
Validate systematically
Communicate compellingly
Adapt continuously
Maintain discipline through uncertainty

This course gives you the methodology to be one of them.

It won't tell you exactly what to do (only you can decide that). But it will help you:

Ask the right questions
Gather the right evidence
Make better decisions
Learn from feedback
Stay oriented toward creating real value

The world needs what you're building.

The challenges we face in health, food, materials, energy, and environment require deep tech innovation. They need scientists and engineers like you, to be willing to step out of the lab and into the messy, complex, uncertain world of commercialisation.

But innovation alone isn't enough. It must be innovation that creates value for real people solving real problems.

Let's begin! I’m excited, let’s go.

A Course Overview and Key Learning Objectives