Lessons from my favourite books

Hey everyone,

I thought I would share the lessons I have read from some of my favourite books.

Originals by Adam Grant

As someone with a strong bias to action and a tendency to start several projects at once, this book helped me temper my bias. Adam Grant outlines a study where he looked at university student grades and revealed that those who take time to finish their assignments, start early but finish last minute obtain the best grades

He calls this approach moderate procrastination and it's one I have been employing to provide structure to my decision making. When I get a new idea, I am excited and biased to launch right away. Instead, I wait, letting the idea simmer in my subconscious. I launch if the idea still sounds good after a few weeks. Its brought more balance, certainty, and clarity to my life.

Hard Thing About Hard Things by Ben Horowitz

I read this book last year after I closed my startup and instantly regretted not having read it earlier my in life. Ben argues for brutal honesty with others and more importantly yourself. Sam Harris is another figure who argues for this approach to life. 

Being radically honest with my actions has been a blessing, another concept here is emotions/thoughts follow behaviors. This is somewhat contradictory to my previous point but at times the best way to know the path is to test them out one by one.

Man’s Search for Meaning by Victor Frankl

After my startup closed down I had a crisis of purpose. I read a few books on purpose/ meaning in life but this one provided me the most clarity. 

The book is an emotional and at times tough read but the lesson is clear. The ultimate meaning and purpose in life come from the people you love. 

Naval Ravikant's Almanac

Naval has a bit of a cult following in some communities but I find a lot of wisdom in his words. To start he argues that creating wealth is a positive sum game and a rising tide lifts all boats. 

To create this wealth, identify your specific knowledge and monetize it. Specific knowledge is found by following your curiosity and learning by experience. Being a physician is an example of specific knowledge. The next step after identifying it would be to create a product that separates your time from your specific knowledge. 

Zero to One by Peter Thiel

Peter Theil is famous for his mantra, "contrarian truth". He argues that a successful startup requires building something truly novel. It requires identifying a pain point no one is solving and then building a product around it.

There is wisdom in essentially building markets where there is no competition. I would caution against first mover advantage as at times you may be paying for expensive mistakes which your future competition can learn from.

Nonetheless, there is an inspiration in building something truly novel, and with discreetness, your learnings could be protected.

Angels by Jason Calanacis

I read this book early on in my angel investing journey and it's the reason I have kept going. Jason argues for diversification within reason here, specifically, he says if you're going to invest in startups then be ready to invest in 20.

This is a numbers game to an extent. You are generally betting on founders trying to achieve something very few do. Recognize this and support your founders, at times this support simply looks like listening to them without judgment. 

Good to Great by Jim Collins

Start with the who, step one to building a great company is getting the right people together. The importance of the founding team, their interpersonal dynamics, and their commitment cannot be overstated.

Jim also talks about leadership, in short, great leaders have a quiet fortitude about them built through discipline, perseverance, and humility. Great companies also create a flywheel effect, they are not one-hit wonders. It's important to build and incentivize processes that reward constant iteration and improvement.

Start with Why by Simon Sinek

I just finished reading this book last month and it has had a profound impact on how I think about taking on new projects. Simon describes what he calls the golden circle, at the center is "why" followed by "how" and "what". 

The simple premise here is that before planning what you are going to do and how you are doing to do it, figure out your why. Simon argues that customers buy why a company does what it does and not what it does. This is congruent with a common sales tactic where you do not sell features but sell a solution to your customer's problem.

He argues for building a company with clear values, beliefs, and mission. Give your customers a place to belong, a place where they can identify with your why. 

The Power Law by Sebastian Mallaby

This is arguably the best book about the history of venture capital and its rise to prominence. Sebastian shows how innovation rarely happens from industry experts but generally starts from an outsider's perspective.

Although not mentioned in this book, I find the story of the Wright brothers vs Samuel Langley an amazing case study to explore the above concept. Another concept explored in this book as the name suggests is the power law. Your batting average is irrelevant in venture capital, it's all about your ability to hit home runs. 

In venture capital, your returns do not follow a normal distribution. A small minority of your investments (maybe even one) will dictate the vast majority of your returns. If you invested $50,000 in Uber during their initial raise you would have $250 million. All your remaining investments would most likely be inconsequential. Venture Capital is a game of essentially finding a needle in a haystack, a high-risk tolerance where you see a substantial percentage of your investments fail is a must. 

Secrets of Sandhills Road by Scott Kapoor

Scott does an amazing job of outlining the importance of a big market. To follow my previous points, in addition to finding exceptional founders capitalizing on an undetected value proposition, a large market is essential.

Generally, we look for markets with more than 10 billion in market cap, given most of your investments will not return significant capital. The ones which do need to return a very large amount. Scott also provides some valuable advice for startups, to raise enough money to get to the next round. Raising at an excessively high valuation can be damaging and few recover from down rounds. 

Influence by Robert Cialdini

Influence is by far one of the most useful books I have read. The graphic above outlines the six principles of marketing. I used these principles in my startup and am currently using them for HealthTech Investors. This newsletter follows the principle of reciprocity where I freely share my experiences and knowledge. I did a Linkedin Post recently, outlining how I am currently using these principles. 

Thinking Fast and Slow by Daniel Kahneman

Daniel provides an excellent framework for when to rely on your intuition in decision-making. While a structured diligent process is necessary to evaluate opportunities, there is a role for intuition as well. He separates environments into high and low validity. 

A high-validity environment is ideal for intuitive decision-making. It is defined as predictable, stable, and one where results are available soon. Seeing patients in a high-validity environment whereas hiring an employee is a low-validity one. 

Thank you for reading,

Rishad

AI and Healthcare

There has been lots of noise recently with generative AI in healthcare. More recently we are seeing the proliferation of AI scribe startups.

We are most certainly at a precipice of sorts where the future of healthcare delivery is uncertain. Nonetheless, I am confident the future will be tech enabled.

We are also seeing platform startups like Hugging face and Healthcare Universe reducing barriers to entry for software applications. 

While previous the prowess of software engineering within the founding team was a useful marker for success, this is less certain now. My diligence framework is shifting more towards startups with a significant data moat and ones which prioritize distribution.

I believe a AI scribe for clinical encounter unicorn is inevitable. Specifically in primary care, with the administrative burden rising I am seeing a willingness to pay for such a service.

One caveat I would say is that if the market is evident to me, it is likely evident for several others including you and henceforth the ship for investment as sailed. While I do not believe this is the case, its important to recognize the possibility.

Data room fundamentals

Hey all,

I wanted to give you my framework for looking at a data room. Here is what I look for:

Cap table 
The two main things here are founder equity split and a reasonable (10-20%) employee stock option pool (this is equity set aside to incentivize future hires as the startup grows).

Financials 
At an early stage there generally isn't much, I look at their monthly burn rate and recurring revenue.

Articles of incorporation
Generally I do not invest in LLC's due to increased taxes on my end. I look to see if ther startup is incorporated as a C corp.

Options pool 
As above a healthy option pool is between 10-20% depending on the key hires that need to be made as the startup grows. If there is no option pool then once can be created.

Team Bios 
At this point I have already spent significant time with each founder. I am mostly looking for founder problem fit, founder market fit and if the team has complimentary skills.

Intellectual property/ patents/ trademarks
The defensibility and exclusivity of IP is important. If IP is borrowed/ was created from previous research or university then I look at the exclusivity of the contract and its cost. Generally single digit equity/ royalties are reasonable, if there is a royalty it must have an expiration date.

Investor Terms 
I look at previous investor terms and if there is a lead (for this round) the current terms. The key things here being pro rata rights (generally are triggered at a certain cheque size), liquidation preference (specifically if previous investors have a fully participating liquidation preference) and if there is a most favoured nations clause.

Other important terms are the valuation (pre or post money), right of first refusal, anti-dilution provisions (generally these should not exist outside of down round protection), preferred to common stock conversion terms, dividends (generally startups do not pay out dividends as the focus is growth), board composition, voting rights (watch out for super voting rights) and drag along rights.

Customer/ partnership agreements 
I am mostly looking to corroborate what the founders have said here. I am also trying to estimate future revenue here and look at the termination terms.

Employee agreements  
All IP/ materials created must be owned by the startups and not the employee. When it comes to founders, all equity must be vested at least over 4 years with a 1 year cliff (they get nothing if they leave before 12 months).
 

Thank you for reading,

Rishad

HTI Pitch Competition Finals!

Hey everyone,

Incredibly excited to announce the top 3 finalists for our pitch competition: 

Tim Fitzpatrick at IKONA Health is building AI/VR solutions which will drive patient activation, empowering patients to be more informed about their health and accessing more care at home.

Andy Olson and Kristin Brogaard, PhD at Inherent Biosciences, Inc. are building an AI enabled epigenetic platform for the future of diagnostic and therapeutics. Their first product SpermQT is identifying significantly more male factor infertility.

Vince Hartman, Ritika Poddar and Giordana Pulpo at Abstractive Health are building an AI enabled SaaS solution which summarizes a patients history, saving physicians time, increasing revenues and improving healthcare.

Amit Garg from Tau Ventures joined me for a fireside chat and here are the take aways:

1. Pro rata rights are an important factor in portfolio construction.

I spoke about pro rata rights previously and will expand on portfolio construction at a later date. Another concept to explore here is conversation rate, essentially what percent of your investments do you forsee "converting" to future fundraising rounds (pre seed to seed to series A and beyond). 

2. Realistically one person can manage 10 companies/ boards. 

I think this is self explanatory, my experience so far helping/ advising entrepreneurs leads me to believe that a considerable amount of this time is likely managing people, emotions and expectations. Launching and growing a company is an emotional rollercoaster and finding stability is difficult.

3. Maturation in the ecosystem is driving the specialization of funds.

This one is very insightful, where I find most still consider investing alongside the "power law" to be true. While the statement isn't against the power law per se, it leads me to believe just investing broadly within a vertical is an unlikely strategy for success. As the market matures, so do the sales processes and commercialization pathways. To succeed, a better knowledge of the path to product market fit is helpful.

4. The best picks are "just plausible", consensus not unanimity.

Risk is inherent in startup investing. Especially in early stage, the old adage “No risk, no reward” rings true. Looking for certainty in seed stage startups is an exercise in futility. If you find certainty, the most likely explanation is that:

A. You are missing something and with enough diligence you can always convince yourself to not invest.

B. The startup is too late to market.

Incredibly thankful to our judges, taking the time out of their busy schedules to support us. In my humble opinion, they are truly amongst the best investors in healthcare currently:

Amit Mehta, MD at Builders VC
Sharon S. Huang at Tau Ventures
Xue Hua at Propel Bio Partners
Ricky Mehra at Continuum Health Ventures

Special thanks to Saumitra Thakur at MedMountain Ventures for stepping in last minute to give closing thoughts!

Thank you for reading,

Rishad

Lessons learned from veering off the clinical path

Hey everyone,

This newsletter is a bit different but I think its important to compare the clinical world to the business world. I know a lot of clinicians are looking to venture out in the business world and I hope my experiences can help avoid mistakes.

Here are the lessons I have learned on my path so far:

1. I can learn from every conversation, either about a new idea, industry or about myself. The main thing I would say here is that the purpose of a conversation/ sales pitch is to understand where the other party stands and to achieve clarity on next steps. 

If I disagree with something that is being said, I will say "I am going to push back on that" before I say my thoughts. 

Active listening is a super power, I am surprised by how many times I still catch myself not listening. It's something I am working on and being a great active listener is critical. 

2. Writing is invaluable and stimulates clarity of thought and ideas. Three years ago I barely wrote apart from my clinical charting. The traction I have achieved thus far is largely due to writing my thoughts and publishing them on social media, in particular LinkedIn. 

I find writing provides an immediate feedback loop and I recommend everyone to write down your thoughts and to make it concise. The fewer words you can use to articulate your ideas the better in general. 

3. The world isn’t as manufactured and planned as I once believed. This is an empowering realization as it opens doors for tremendous opportunities to make things better.

4. Behind all movements, decisions and actions there is simply a human being. Most of us have similar desires, wants and at times biases. Recognizing when these are driving our behaviour is critical.

5. Be clear with your goals/ intentions and expect the same from others. I find so many of us let external expectations and reactions influence are behaviours.

I find that people still value authenticity, transparency and honesty. If you're clear with your ideas, you can demand the same from others. 

Ambiguity within your team, not knowing where everyone stands is very dangerous and you can only progress once there is clarity. 

6. Hire primarily for commitment, not talent, knowledge or skills. The exceptionally talented but selfish individual should be let go. 

I won't say too much here, but commitment to the mission and team is the biggest predictor of success early on. This is something I look for in founders as well. Most of us have the aptitude to develop the knowledge and skills if we are committed. 

7. A bias towards action is generally a positive but can be a negative when taken too far. As someone who has a very strong bias towards action, I routinely risk taking on too many projects and not being able to deliver.

It's important to roughly plan the resources, capital and time I will need to deliver on a project before I launch it.

Once you decide you have the time needed, then I would launch. There are some things you can learn from others, but some things you have to learn by doing.

I will say selling, hiring and firing are 3 things you have to learn by doing. 

8. Define your success. I am still surprised by how little I had thought about what success means to me when I finished residency. 

I find the Japanese concept of Ikigai to be a good framework here. Ikigai is a word for "reason for being" and it exists at the intersection of what you love, what you're good at, what the world needs, and what you can be paid for.

Final thoughts

I hope the above is helpful for everyone reading. I am planning a fireside chat with a couple physician friends who are now venture capitalists and will announce it soon. 

Thank you for reading,
Rishad 

Angel investing portfolio construction

Portfolio construction is often an overlooked part of angel investing but I think its critical to maximize returns. While venture capital has a lot more intricacies and the following is geared towards angel investing. 

While inevitably your first or second investment may be driven by excitement for a new idea, its important to have a structured approach in planning the cadence and amplitude of future investments. 

1. How much will you deploy?

Step 1 of portfolio construction is determining your total pool of capital. In the venture capital landscape this is your fund size. For angels this is the total amount of capital you want to deploy towards your angel investments.

Personally, this is 15% of my net worth at this point. It's crucial to have this number in mind or you risk deploying your entire pool in the first three investments. For the purposes of this newsletter, let's say you will invest $1,000,000 over the course of your investing journey. 

2. How many investments will you make?

Before we talk about your number of investments, we have to talk about the power law. Returns in startup investing do not follow a normal distribution, instead a small minority of your investments will drive a large majority of your returns. This is a game of hitting grand slams and your batting average is irrelevant.

Generally, if you are "good" at this game you can expect 10% of your startups to fail, 80% to return 1-2x and 10% to return 5x+. From a venture perspective, generally the target is certain percent ownership (usually between 1-10%) till exit.

To maintain this ownership, you have to invest more money in future rounds of financing. 

Another method would be to not worry about maintaining this ownership and factoring in a 20% dilution per round x 4 rounds before exit. I will skip the math here, but this results in maintaining 40% of your initial ownership stake at exit. Say you invested 100k at a 1 million valuation, you own 10% of the startup.

If the startup doesn't raise another penny and gets acquired for $100 million, you get $10 million (from your 100K initially invested).

Generally the startup will raise more rounds and your equity will get diluted 20% per round. If the startup raises 4 rounds before exit, your 10% will be diluted to about 4% (10 - 8 - 6.4 - 5.12 - 4.096) and your initial investment will return $4 million. 

Now if you maintained your "pro-rata" or 10% ownership stake you would still return $10 million, but you would have to invest more capital to do so. Let's say the valuation at the next 4 rounds was $4M, $10M, $20M and 40M.  

To maintain your ownership you would have to invest 4M (300K, 600k + 1M + 2M). Now you've invested 4M to return 10M. In this specific scenario, you might say it doesn't make sense to invest in the following round, or perhaps you just want to invest in the 2nd round and then forego your prorata. As you can see this can get complex fairly quickly. 

Most angels chose to simply invest early on and do not follow on. Going back to our proposed $1 million investment, a simple straightforward approach could be to invest 50K in 20 startups at a median valuation of 5 million targeting a 1% initial ownership and recognizing that ownership at exit will likely be 0.4%.

If 2 of those startups exit at a $500 million valuation, you've returned $4 million, 4x your initial investment (likely over 10 years) given all the remaining startups return nothing. For comparison if you invested this $1 million in the S&P 500 you would return about $2.1M.

Now the above scenario is contingent on being "good" at deal flow, diligence and value add post investment. It's impossible to predict early on which startups will fall in the 10% as external events/ tailwinds will drive a considerable amount of success. 

Final thoughts

Figuring out how many investments at what target ownership is an important part of startup investing and you should ideally model out a few scenarios to see which one appeals most to you. I am a proponent of investing alongside your risk tolerance and following a detailed analysis at times picking the strategy you're most excited about is preferred. 

I hope the above provides some clarity and gives you a strong base to launch your angel investing journey.

Thank you for reading,
Rishad 

How to identify and mitigate risks in healthcare startups.

A big part of early stage investing is identifying and mitigating risk. While risk is inherent in all startups, knowing which risks are acceptable and which ones aren’t is key. Below, I outline the what and why for a thorough early stage due diligence process. 

1. MARKET RISK

Market timing is crucial for startup success. I always ask founders, “Why now?”. What tailwinds are you banking on which will drive market adoption?

We spend a considerable amount of time evaluating if the market is ready for this product and identifying market trends. Knowing what the market adoption pathway looks like is also important.

To put it simply,

Great founder + bad market = Market wins

Market size is also important and can be difficult to determine for disruptive/novel technologies which will create new markets.

2. TEAM RISK

The main thing I look for here is founder-problem fit and to a lesser extent founder-market fit.

If the market is ready and the founder is capable, focused, humble, formidable and reflective I believe this will transition to traction and product market fit.

We are not growth experts and I plan to leverage my network post product market fit to ensure a smooth scale/growth phase before exit.

3. PRODUCT/TECHNICAL RISK

I will usually start my risk assessment with this step. I look for founders who are problem focused but customer obsessed which I find results in the best products.

A simple question here is:

Can this team build this product?

I follow my curiosity and keep digging deeper. At times it’s natural to want to take mental shortcuts but I personally only invest in things I understand and will continue digging until I am satisfied.

4. COMPETITIVE RISK

Having an in depth understanding of competition is important. A crowded market or empty market are both signals for an unfavourable competitive landscape. Commonly, people say there’s a significant new mover advantage in new markets.

Unfortunately we haven’t seen this translate to successful exits in the past. Some well known examples being Google and Facebook - there were over 15 search engines before Google and many social media platforms before Facebook.

For healthcare, telemedicine has been around for more than 20 years, but adoption and successful exits have only started to happen recently with an emerging tailwind driven by the covid pandemic.

In short, first mover advantage is a myth.

We look for growing markets with a few competitors.

5. DEFENSIBILITY RISK

This speaks to the question, why is this startup different?

Let’s start by talking about patents. A good patent strategy is important but is not the be all end all. Generally speaking utility patents are more defensible than design patents. Software patents are generally difficult to defend, and the defensibility lies in the code itself.

Strong network effects are hard to replicate and could be a sign of defensibility.

Going deep into the due diligence process, looking at defensibility is where you’ll start to uncover the uniqueness of a particular network effect.

6. REGULATORY RISK

Startups should have a good understanding of a registry pathway to market. Most startups will choose a Class 2, 510k pathway. There will be a predicate for this pathway and we look at the predicate and the differentiator from it. A Class 3 pathway, while novel and disruptive, needs significant funding and time before market, and requires more conviction that the product they’re making solves the problem 5-10x better than the current standard.

Thank you for reading!

Rishad

My decision making framework

Hey everyone,

The hardest thing about investing in early stage startups isn’t which questions to ask or which framework to use in your due diligence process.

While a thorough due diligence structure is important, recognizing when you’re making assumptions, using your intuition and when to trust it is critical.

We are naturally programmed towards over-indexing for convenience and energy conservation. At times, we don’t perceive thinking as significant energy expenditure. This is a fallacy as professional chess players burn more than twice as many calories per day as marathon runners.

As humans we have a strong inclination towards taking mental shortcuts, making assumptions and using intuition. It’s imperative to recognize when you’re using intuition and to validate it.

Here is what I ask myself when I use my intuition: 

1. Am I an expert in answering this question? I use the 10,000 hour rule here as it has some evidence and provides me with a repeatable signal. 

2. Why is my intuition telling me this?

3. Does this question exist in a low or high validity environment? 

The last point is borrowed from Thinking Fast and Slow by Daniel Kahneman. He argues that a high validity environment is required to develop intuition. He defines this as an environment which is relatively stable, you are performing the same behaviour repeatedly and you know if you’re right/ wrong fairly soon.

Working as a physician in urgent care is a high validity environment. Generally speaking investing and hiring are not and require a structured approach to decision making. 

There is always a balance between intuition and structure. Looking back the best decisions I have made involved me reserving my intuition till after a structured process.

Thank you for reading.

Rishad

What do I look for in a medical device startup?

Hey everyone,

Here is how I look at a medical device startup from an investor perspective:

Team:  The team/ founder story is as important as ever here. Is there a strong founder-problem fit? 

If there is, the next question I ask myself is: Can this team build their product and can they sell it? Do they have clinical representation from their end user?

Product: Before getting into the product, I ask myself if they are solving a big problem? What is the current solution and is this product significance better? Does the product replace the current standard in its entirety or is it an adjunct? 

Market: This is arguably the most important question. What are the current market trends/ tailwinds and how does this product fit in them? Is this a growing market? What is the competition like? 

Reimbursement: 10 year ago startups in the medical device space did not have to worry about reimbursement as they were generally acquired post FDA approval. There has been a shift in landscape and general consensus dictates a need for commercialization before acquisition offers are on the table. 

 For new technologies, often there is no current reimbursement code, CMS has a 3 year new technology add-on payment program to reimburse these devices. 

If they are using existing codes, then differentiation from the current standard is important. Its important to ask how does this device lead to an increase in revenue or a decrease in expenditure?

Distribution: At the very early stages, mostly what I am looking for is that the founders value distribution. Are they talking to potential customers? Do they have any letters of intents? A good distribution network translates to more feedback and faster iteration cycles. Speed of iteration is a known marker of startup success. 

Workflow: How does this fit into the current work flow? This often goes hand in hand with reimbursement. There is balance here on ensuring the current workflows are not disrupted but there is a tangible clinical benefit. At the end of the day, for medical devices in particular success is contingent upon adoption by end users (often physicians). This is also why having clinical leadership is incredibly important. 

Exit:  The general path to exit here is acquisition. Again, this is another place where healthcare and medical device in particular is different from other industries. These relationships take time to build and startups needs to have thought of an exit strategy. From my discussions with medical device players, they are now looking for commercialization before entertaining acquisition except in very disruptive/ de novo technologies. 

Thanks for reading!

Rishad

How to screen a pitch deck

Hey everyone,

Here is what I look for during my initial pitch deck screening:
 

Team: Ideas are a dime a dozen, execution is a magnitude more difficult. The key question is, can this team execute? Can they build this solution, can they sell it and can they do it together?

Does the team have the grit, humility, aptitude and perseverance to see this idea to market? Team dynamics are incredibly important and some things I look for here are: what is the relationship between the founders, how committed are they to this problem, to each other and to the startup, do they have industry expertise. 

Product: The key here is to remain focused on the problem they are solving. Is it a big problem? Is this solution significantly better than the current standard? How does this fit in the current workflow? What assumptions are the founders making and have they validated them with data?

Business model: At its core, the business model should be profitable while the product provides value to its buyer. In healthcare this is often looked at through a financial lens. Does this generate revenue or decrease costs? The former is preferred. There is tension between what patients want, what physicians want, what health delivery systems want and what payers want. The founders should have an understanding of who their buyer is and how they are providing value to their buyer. Note this is different from providing value to their user as the user and buyer are often different. 

Distribution: If you ask first time founders what the most important predictor of success is, they will say it's their product itself. If you ask second time founders, they will say distribution. If you build it, they will not come. While I do not expect founders to have a complete distribution strategy, I want to see they have focused on this and on value. If they talk 90% of the time about the product and mention distribution in passing, this is a yellow flag. 

Thanks for reading and would love for you to join me in the webinar mentioned below!

Rishad

What you need to know about FDA approval

Hey everyone,

While learning about the different FDA approval pathways might not be the most exciting thing you may do today, I think it’s critical to know if you want to be a great early-stage healthcare investor.
 

Class I: This is the lowest risk category and generally doesn’t require pre market approval or clinical trials. These poses minimal or no risk to patients. Approval for this can happen ask fast as a few months and $10,000 through a 510k pathway(explained further below). 

Class II: These are moderate risk products which affect patient health but are not used in life threatening or critical conditions. Class II devices fall into 510k, de novo or pre market approval pathways.

Class III: These are high risk products and often involve life threatening and sustaining therapies. There are generally 2 pathways here, PMA and HDE(humanitarian device exemption). This always requires robust clinical trials.

510k pathway can be used for all classes and is  used for products where a similar product(predicate) already exists in the market. The FDA charges between $4,000 to $12,000 for this pathway and generally it takes between 2-6 months. For a class II device, the median is 2.5 years and cost is $3 million. While clinical trials are not needed, they may ask for clinical data. They may also ask for post market surveillance. 

De Novo pathway is used when there is no similar existing product. This may require clinical trials. It generally costs a few hundred thousand to a few million. The time varies but at minimum it would be 6 months up to 5 years. For a class II device the median time is 5.5 years and cost is $5 million. 

PMA(pre market approval)  is the stringest pathway, the cost runs into 10s of millions and it’s a lengthy/ arduous process. This pathway requires clinical trials. Generally this is used for class III devices.

Breakthrough Devices Program: The is intended to expedite the process for products which have the potential to improve treatment for life-threatening or irreversibly debilitating conditions. The FDA aim to make a decision within 45 days. Generally this would require clinical trials and cost a few million.

Humanitarian Device Exemption (HDE):The HDE pathway is used for products designed for rare diseases(less than 8,000 people per year). The timeline is about 12 months and costs vary depending on if a clinical trial is needed.

Thanks for reading,

Rishad

Should healthcare be profitable?

This is a topic I have been thinking about quite a bit. Being involved in the startup and now early stage investing world, I have a close relationship with growth and profits in healthcare.

A profit motive is necessary to drive innovation and efficiency, by doing so it improves clinical care. On the flip side, it can limit access to care as companies will charge the optimal price to maximize profits. 

I think both incentivizing innovation and improving access to healthcare are non-negotiables when it comes to designing a financial model for a healthcare system. To align profits and access we need to ensure life-long insurance coverage, a no deniability policy and equal access to basic healthcare.

Tiers of healthcare are inevitable in a for profit system, we need to ensure the most evidence based treatments are ubiquitous. We need a system where "basic" healthcare is accessible to all and people have the ability to pay for "bells and whistles".

Lets do deeper on access to care, in Canada (a wholly publicly  funded model) wait times are one of the longest amongst developed nations. In US, while they are substantially shorter, they are contingent on the "type" of insurance you have.

Interestingly the shortest wait times are not in the US, but in Switzerland and Germany. The Swiss model of healthcare is fascinating and one I propose makes the most sense. Why it hasn't achieved greater penetration abroad is a mystery to me right now. 

While Switzerland has universal healthcare, each resident is mandated to purchase their own health insurance. This cost is subsidized by the government when needed. People have the freedom to choose their providers and switch as they want. The whole country is "in-network".

My thoughts at this point are that this models is the most practical and efficient I have come across thusfar. 

Thanks for reading,

Rishad

What is a liquidation preference?

This is one of the most important terms in a SAFE/convertible note and is often overlooked.

It provides us with a way to return some capital if the startup fails. Generally only holders of "preferred shares" get access to a liquidation preference, and holders of "common shares" so not. 

Liquidation preference outlines the order in which investors get paid and at what multiple of initial capital invested, when there is an exit. There are four parts to a liquidation preference:

Seniority structure (who receives their money first):There are 3 types of seniority structures. In a "standard structure" the investors who invested last receive their liquidation preference first. So the earliest investors lose out. In a "pari passu" every investor is treated the same and gets money back in proportion to their investment. Tiered is a mix of the two above.

Multiple:this one is easier, you will receive a multiple of your initial investment if you exercise your liquidation preference. Generally its 1x, sometimes it might be 2-3x but this can lead to resentment from other investors who don't receive this and is uncommon.

Cap:sometimes there will be a cap to your returns, this protects the founder. Usually it's a multiple of the initialinvestment.

Participation:You don't necessarily have to exercise your liquidation preference. There are two types here, non-participating liquidation preference vs full participation liquidation preference. In a non-participating liquidation preference you can either a) exercise your liquidation preference or b) convert your preferred shares to common shares. Depending on the valuation at the liquidity event, it might make sense to pick either option. A full participation liquidation preference allows you to receive your liquidation preference plus a proportion of the remaining funds divided proportionally amongst remaining common shareholders. Generally there will be a non-participation liquidation preference.

Let's go through an example, say you invested $1M for 50% of the company at a 1x liquidation preference with a 3x cap. Let's say the company exits at 10M.

If you were to exercise your liquidation preference, you would receive 3M total as you're capped at 3x your investment. In this scenario it would make sense to not exercise your liquidation preference, instead you can convert your preferred shares to common shares and receive 5M(50% of 10M). The point at which you will get paid more if you convert your preferred shares to common shares(instead of using your liquidation preference terms) is called the "conversion threshold".


Thanks for reading,

Rishad

What are pro rata rights?

To understand pro rata rights we have to first understand how dilution works. Say you invest $100,000 in a startup at a $1,000,000 valuation thereby owning 10% of the company with 100,000 shares at $1 each. The founders own the remaining 90% and 900,000 shares.

Let's say they raise their next round from a new investor(A) at a $2M valuation and give away an additional 10% equity for 200K.

Now they will create 111k additional shares so that A owns 10%(111,111K/1.11M)). The total outstanding shares is now 1.11M shares and your ownership is 100,000/1,111,111 = 9.0%. Your equity is diluted by the same percent that is being given away at the next round.

You now own less of the company, but your shares are valued at 9.0% of 2M which is $180,000. Pro rata rights give you the ability to maintain your ownership percentage so when the startup raises the next round they have to "allow" you to contribute more funds at the new(2M) valuation so you can keep your ownership at 10%(the initial ownership).

Investing money in subsequent rounds is called follow on and is generally good practice. The further the startup goes the better the chances of success. Once venture capital money flows in the chances of success rise substantially although its still high risk with the best VCs now returning any money on 50% of their investments.

Dilution can be tricky to understand and it took me a while, feel free to reply to this email with any questions. Things get a little bit more complicated with pre and post money valuations but I've kept it as simple as I can for now. 

Thanks for reading,
Rishad 

Startup Metrics to Know

Generally I will ask the founders about the metrics below. Keep in mind this is for an early stage company raising at under a 10 million valuation.

BURN RATE

This is expenses - revenue. A high burn rate is red flag and I will usually ask more questions if they are burning through say 100k a month. Its easy to burn through cash and I look for financially responsible founders.

RUNWAY

This is essentially how many months of cash they have left. In the current environment they should have at least 12 months ideally 18-24 months of cash left once they are done raising.

CUSTOMER ACQUISITION COST (CAC)

How much does it cost (usually in marketing/sales/ads) to bring on one customer. There are only so many channels of acquiring customers and organic traffic (such as through partnerships or ranking high on google search) is much better than traffic through ads (google ads/facebook ads etc).

LTV/CLV

Customer lifetime value is how much money will 1 customer generate over their lifetime. This should ideally be at least 3 times CAC.

CHURN

What percent of customers are you losing every month/ year. Depends on if the startup is direct to consumer or business to business. The annual churn should be around 5-10%, the lower the better. A monthly churn of 10% may sound low but is fairly bad as it means in 5 months you will be down to 60% of your initial customer base (90%-81%-72.9%-65.61%-59%).

RUN RATE

This is how much revenue is the company generating (monthly/annual). This is also a way to value the startup, for an early stage fast growing startup you can use a 10-30x multiple. Although this multiple changes somewhat with the public markets/ exit potential.

Thanks for reading,

Rishad

Two questions I ask every founder trying to sell into healthcare.

If we were to break down an early stage startup, the two essential components are sales and product. Most founders focus too much on product and not enough on sales. If you build it, they will not come. A good sales plan can make or break a startup. The following applies to founders trying to sell into health systems. For both these questions, ask more details, get granular and let them talk. 

Here are two questions I ask every founder:

1. What is the clinical benefit? - This one is obvious, how does this product/ service improve healthcare? One thing to focus on here is how the solution fits in the current workflow. Does it require more resources from the customer? Does it replace existing workflows? If so, how do the founders quantify their solution is better? 

2. What is the financial return on investment for the customer? - I generally try to go deep and get granular with the founder here. Ask them in detail how their solution will improve the financial health of their customers. If they are using a CPT code, ask them which code.  We can break down financial return into 2 categories:

• Increase in revenue: if the solution increases revenue, how is that revenue captured? Are they billing the patient directly? Are they billing insurance, if so which codes are they using and how much does the code pay? Founders here will at times downplay the staff cost to onboard and maintain their solution. Does it require a nurse/ clinician? Will it take time from IT? All these costs need to be accounted for.

• Decrease in expenditure: this generally requires a change in the existing solution and healthcare systems can be somewhat allergic to change. I ask them to lay out the existing solution in detail and then quantify how theirs is better. Again pay attention to any changes in staff workflow. If the sole proposition is that it makes the clinician/ nurse's job easier/faster generally this unfortunately won’t translate to a financial return. A solution which reduces missed appointments/surgeries/readmission is more likely to have uptake as there is a short term tangible financial return. 

Thanks for reading,

Rishad

How will artificial intelligence impact healthcare?

Artificial intelligence has been touted as the cure to our healthcare crisis for a couple decades now. Recently there has been some progress made with diagnosing certain conditions (diabetic retinopathy/eye changes in diabetes, otitis media/ear infection and cancer detection). Even with the recent advancements, adoption remains spotty and any actionable steps continue to require considerable physician input. 

In a previous podcast with Amit Garg from Tau Ventures, we discussed the concept of explainability in the realm of artificial intelligence. For a long time, we held on to the notion that we need to understand the learning processes (neural networks, decision trees, linear regression) behind artificial intelligence. While I am far from an expert on this, a neural network (one type of machine learning) is essentially a black box. If we require explainability as a precursor to adoption (FDA approval in healthcare) then we limit the scope of AI immensely. 

I recently spoke with Amit Mehta from BuildersVC, he has considerable experience with artificial intelligence as it pertains to the FDA approval process. The FDA has given approval to several imaging technologies which help physicians in decision making. Here are some takeaways from our discussion.

• Identifying potential diagnosis is version 1 for AI. This version answers the question, eg. "is this cancer?"

• Version 2 will lead to predicting prognosis, if version 1 says “Is it cancer or not right now”, version 2 will say “Will it ever become cancer”. Currently we are at version 2. 

• Version 3 involves A.I making clinical decisions. Using the above example, version 3 might say “This mass is cancer, it requires a biopsy within 2 weeks.” 

Zooming out and looking at our system as a whole, there is an immediate need and opportunity for version 3 AI  replacing our algorithmic decisions. An example could be a prescription refill for birth control. This is a very exciting time to be in the healthcare space, we predict the next 5 years will bring on version 3 AI, thereby improving access to care on a global scale.

Thanks for reading,
Rishad 

The future of healthcare given the worsening clinician shortage

Healthcare needs a “triage” system which shares enables patient decision making with no physician involvement. Our current system with physicians often being the first point of contact is incredibly inefficient, expensive and not sustainable.

The future of healthcare lies in empowering patients to control their health. Let’s take Sam for example, she is 50 years old and takes Ramipril (a blood pressure medication) for her high blood pressure. She has no other medical issues.

Her doctor sees her every 3 months for a refill. She asks Sam if she has had any new symptoms and what her home blood pressure readings are. Once a year she orders some blood tests. The main thing we look for in someone taking ramipril is kidney function. The two main side effects of ramipril are a lingering dry cough and rarely but potentially dangerous  condition called "angioedema" where your face/lips become swollen.

Usually this is the entirety of Sam's visit unless new issues come up. As the healthcare staff shortage worsens either:

1. The frequency of these visits will lesson
or
2. Physicians will stop taking on new patients

Given our liability environment, the second option is the more likely future. This will leave a substantial number of patients without care and we need a solution which doesn't rely on more clinicians (as this is sadly wishful thinking).

The most likely solution is that Sam is given information on high blood pressure and Ramipril. She is informed of the above monitoring parameters/ side effects and empowered to treat her own high blood pressure. She is assigned a "patient navigator" with minimal clinical training who answers preliminary questions. If needed she is seen by a clinician, but this is the exception not the norm.

How to evaluate first time founders

First time founders have a very difficult journey ahead of them and most of them to not succeed. Early on in a startup, the only two things that really matter are product and sales. While experienced founders with successful exits get a pass, for first time founders, the founding team needs to be able to build and sell the product. Once they pass this initial screen (Can they build it? Can they sell it?), here are the things I look for in a first time founder:

Founder-problem fit: launching a successful startup is very difficult and those who have not done it before will generally go through many challenges. Commitment to the mission/ problem is very important and one of the best predictors of startup success, Adam Grant touches on this in his book Originals.

Perseverance: the startup journey involves lots of highs and lows. To push through requires extreme perseverance. Early on in my startup we had a few verbally committed pilots fall through for little apparent reason. I would've likely given up at that point if I didn't identify deeply with the problem we were solving (improving access to healthcare).

Ability to learn: this goes hand in hand with being humble. Knowing what you don’t know and having the skill to learn it is a superpower. This requires a keen eye to separate signal from noise, with so much information out there, learning from inaccurate sources can be incredibly damaging. A scientific background helps here, expert opinion is the lowest form of knowledge and systematic review one of the highest.

Ability to apply knowledge: education without application is wasted. The ability to take what you’ve learned and put it into practice is invaluable. While learning for its own sake can be rewarding, you need to be able to apply lessons learned to improve your chances of success.

How they face uncertainty: launching a startup is an irrational endeavour which requires a high risk appetite. There will inevitably be times when decisions have to be made where both choices appear wrong. A calmness in the face of uncertainty which comes from a high risk tolerance is a must.

While founders come in all shapes and sizes, my theoretical and practical experience has led me to look for the above things. As usual, there will always be exceptions but we should not be distracted by them when forming our investment philosophy.

Thanks for reading,
Rishad

Story of ClinicUp

After I graduated from residency I worked in various different clinical settings from hospital medicine to family medicine clinic.I landed on hospital medicine but as I gained experience I started to get more and more frustrated with the inefficiencies in medicine and how we protect the status quo.

There are quite a few things in clinical practice which are based on algorithms and I saw an opportunity to automate some of these. A colleague(A) and I were discussing potential opportunities, we talked about how travel medicine consults don’t require a physical exam and the treatment offered is based on a series of questions.

We got to work and wrote down potential questions and their answers which could be made into a clinical decision tree. Initially we outsourced our development which unfortunately wasn’t successful. At this time a friend introduced me to his friend who was a software engineer(B).

As B came along it became clear that I was doing most of the work and A, although very capable, was not invested completely. A difficult conversation led to A departing with the initial brand and we re-branded as  ClinicUp. The pandemic kept going and travel wasn’t taking off. Furthermore travel medicine consults are not covered through the government health plan, making customer acquisition more difficult.

We desperately needed help with marketing as well, my amazing wife (who has a background in marketing) offered to help us while raising our newborn. With the help of my wife, we made the decision to pivot to general medicine while thinking of niches in womens health and mental health.

With the pivot and my wife on board our CAC was $5, we started growing exponentially and I hired 10 physicians. Things were looking good on paper but our margins were slim. We were using a white label solution for our tech and as a result had no IP. I was working full time and so was my cofounder(B).

As our work/life commitments began to suffer I realize I didn’t have enough time to do it all. Without IP, selling the startup would be difficult. We got a potential $6 million offer and were over the moon. Then we got sued, a frivolous lawsuit from a potential competitor. Nonetheless I didn’t want to spend my investors money on a sinking ship and we decided to close.