Torys’ Tips™: Cross-Border Funding for Life Science Companies

By Cheryl Reicin and Adam Falconi

If you plan to do business in Canada and the U.S., you may already have (or are planning to set up) an entity in both jurisdictions. When preparing for a cross-border financing round, you will often have to decide whether the investment should be made in your U.S. or Canadian entity. Most commonly, the investments are made at the parent company level.

So, which company should be the parent company, and which should be the subsidiary?

Here are key considerations to weigh:

• Ideally, you will want to determine the appropriate jurisdiction for your parent company when first setting up your business. While you can change the parent company's jurisdiction at the time of a financing round, it is best to do so before there is significant value in the company so that you can avoid adverse tax consequences. For example, if a Canadian company with Canadian shareholders wishes to reorganize so that it has a US parent company, the Canadian shareholders will be subject to tax for the increase in value of their shares when they exchange the Canadian company shares for those in the U.S. company. This tax will be applicable regardless of whether such shareholders sell their shares.
• To receive reimbursable and enhanced Scientific Research and Experimental Development (SR&ED) tax credits, a company needs to be a Canadian-controlled private corporation (CCPC). The rate for. enhanced reimbursable SR&ED credits is 35% federally for qualified expenditures and each province has additional reimbursable tax credits for CCPCs. Although it may be possible to implement corporate structures that allow a company to access enhanced SR&ED credits with a U.S. parent company, this structuring can be complex and costly.
• U.S. shareholders will not be able to access capital gains exemptions under the Qualified Small Business Stock (QSBS) regime if investing in a Canadian entity.
• Canadian shareholders will not be able to access the lifetime capital gains exemptions for Qualified Small Business Corporations (QSBC) if the shares are held in a U.S. corporation.
• Corporate law in Canada is very similar to Delaware corporate law (the jurisdiction of choice for most U.S. corporations), with recent changes in Ontario and Alberta corporate law bringing them even more in line.
• Many cross-border tax-related issues, such as withholding taxes and PFIC status, have been. addressed by changes in laws in both jurisdictions, allowing for less obstacles in doing business.

In addition to determining if investments should be made into your U.S. or Canadian entity, there are several other cross-border fundraising considerations to keep in mind.

U.S. versus Canadian dollars?

- The price of shares and options can be set in either U.S. or Canadian dollars, regardless of where your parent company is. However, using multiple currencies can create accounting complications.

Where should you hold your intellectual property?

- We generally recommend that companies hold their IP (including U.S. patents) outside of the U.S. due to higher U.S. corporate tax rates and the difficulty of moving IP outside of the U.S. at a later date. For these reasons, Canada is generally preferable to the U.S. as an IP holding jurisdiction.

Canada may soon become even more attractive as the Canadian government is currently considering the implementation of an “IP box” regime that would set lower tax rates for income from IP than for other business income.

Differences in Deal Documents?

The Canadian Venture Capital & Private Equity Association (CVCA) has publicly made available model venture capital documents which are based on the U.S. National Venture Capital Association (NVCA) model documents. Therefore, investment deal documentation will be similar whether investing in a Canadian or U.S. entity.

Each company’s situation is unique and so there is not a one size fits all approach to these issues. The analysis of what best works for each company can be complicated and it is important to obtain advice from legal and accounting professionals who are experts in dealing with cross-border issues affecting life science companies. They can guide and assist you in arriving at the best solution for your business.

For more information on the work Torys does to support life science companies, reach out to our team.

Checking the Climate in Digital Health Technology: August 2022

Kate Gunning,

Managing Partner, Focus Academy LLC

www.focusacademy.bio

The US healthcare environment is evolving and changing since the onset of COVID in early 2020 and Digital Health is an area of rapid change, particularly evident as we are now in the middle of 2022. Keeping on top of the market and the changes that are coming in terms of the economy and the investment landscape, it’s important to keep track of the opportunities and the threats that this sector is.  experiencing post-pandemic.

We have reviewed the recent developments in Digital Health and noted some interesting trends and opportunities being presented in the current changing environment.

1. Digital natives love Telehealth 

Though there was a dramatic increase in the utilization of Telehealth during the pandemic, this has fallen off amongst the older baby boomer generation and older adults. However, according to recent research, digital natives still love the easiness of the Telehealth visit and utilization rates are expected to remain at 73% for the Gen Z and 83% for the millennial generations, while dropping to 51% for the baby boomers.

2. Expanding Telehealth access

Congressional support is on its way for the increase in access to Telehealth services, by extending congressional Telehealth funding for four years instead of two in the US. The legislation also hopes to expand the eligible list of practitioners to include rehabilitation therapists, to expand services for Federally Qualified Health Centers and Rural Health Clinics, to provide virtual hospice visits, and to delay Medicare in-person requirements. Audio-only technology will be provided for places with low broadband capabilities, so that Telehealth services become accessible to all communities.

3. Interoperability

Interoperability is an important component for the expanded use of digital health technology, referring to the seamless exchange of data across organizations and systems. This is an extremely important component to make it easier for patients and providers by making relevant data easier to access without security or privacy problems. Moreover, interoperability in the healthcare industry can reduce the cost of care by minimizing the need for repeated or unnecessary tests and making diagnosis faster.

4. AI promotes early intervention

AI has proven to be most valuable so far in the area of imaging. One of the first computer aided detection AI systems to analyze images gathered during a scan, GI Genius, allows physicians to identify conditions more quickly, promoting early intervention by identifying pre-cancerous and cancerous colorectal polyps during a colonoscopy. The system works by scanning every visual frame of the procedure in real time and alerting physicians to the presence of lesions — including small, flat polyps that can easily go undetected by the human eye. By detecting and removing these polyps, clinicians reduce the odds of patients developing colorectal cancer.

5. Behavioural health is still an area of growth, though there are significantly more players in the space, and they are more competitive. There has been a significant increase in the demand for behavioural health interventions and the business models are changing, i.e., how do these solve the mental health problems, what is the ROI, and the evidence to support progress and improvement with objective metrics.

6. The move in the US from a “fee for service” model to a “value based” model will depend greatly on the adoption of digital health technology. One of the main concerns, though, for the management of chronic disease, is the ability for remote patient monitoring, especially for those living in remote and more impoverished areas. It has been reported that audio only tele-visits were higher among people of color, adults without a high school degree, people with lower incomes and those without health insurance. Insurers are currently only covering tele-visits that use video. This is now a considerable concern for those unwilling or unable to use video for their appointments. The US House of Representatives recently passed a bill to extend the telehealth flexibilities under the public health emergency for another two years.

7. Wearables can empower patients, but adoption is challenging

A recent study of over 7,000 patients indicated that there are three main barriers to adoption of wearables by patients. Researchers found three main overarching themes: the role of providers and potential benefits to care, driving behaviour change and barriers to use.

On the clinical front, it was reported that not all health systems have great track records of adopting new technologies quickly. Healthcare workers would probably need more training to encourage engagement and push behaviour change among patients. The ongoing monitoring and feedback would also add to their workloads, according to the study. It’s also the case that consumer wearables are not calibrated for use in healthcare, which could lead to inaccurate data.

Additionally, it was found that for patients to receive appropriate support, a preliminary assessment is required to match to the wearable device and prevent negative impact of an individual not meeting goals.

Other barriers to adoption indicated that though individuals said they were willing to use wearables, actual use was inconsistent. Users sometimes forgot to put them on, lost them or simply became disinterested. The design, cost and technical and privacy issues could also impair use.

Other notable drivers to watch include:

• Consumer-brand healthcare market players with significant digital capabilities and potential to disrupt traditional healthcare service models (Amazon, CVS, Google, etc.)
• $65B in Federal digital equity funding is making significant investments in broadband development and deployment laying a vital infrastructure for industries such as healthcare to build on
• A shift to deliver more care services outside of traditional setting in home and community-based settings will drive new service models and digital health capabilities (e.g., hospital at home)
• Provider organizations' implementation of enterprise-level digital transformation strategies seek to marry data, automation, and virtual capabilities in a strategy that eliminates friction points in virtual care and transforms data to deliver seamless and personalized care experiences.

2022 saw a dramatic decrease in investment in the digital health sector as opposed to 2021, according to Rock Health’s recent report on the state of the market. As most investors will attest, 2021 was a bumper year and an anomaly and 2022 digital health funding is on track to outpace funding in 2020. Companies are trimming costs and reevaluating their go to market strategies, and there is a slowdown in larger deals and later stage funding. However, the climate is still good for earlier stage investments, according to the venture community and strong areas of investment remain in the areas of digital mental health, pharma R&D solutions and administrative ad clinical workflow solutions. As there were record funds raised by the investors in 2021, it’s expected that “early-stage digital health companies, which are more likely to be free of 2021 valuation baggage are likely to attract investor attention in today’s market.”

                                                                         

Torys’ Tips™: Licensing for Life Science Companies

By Cheryl Reicin and Adam Falconi

As cross-border life science lawyers, we provide support and strategic direction for companies through all stages. This includes corporate structuring, licensing and strategic collaborations, private and public financings (angel, venture capital, public offering, etc.) M&A and joint ventures, and IP management. One common question that life science companies have is how to navigate licensing their technology in a way that brings the highest strategic and economic value.

Below are some of the key considerations to keep in mind.

• An important first step is to clearly map out your goals and business plan so that your licensing strategy dovetails with your business objectives. Licensing can validate and advance your science, provide additional resources to further develop or commercialize your product, and provide extra revenue, amongst other advantages. However, a short-sighted approach to licensing can hinder these benefits.
• Licensing is a flexible instrument that can be customized to suit your company’s needs, so clearly identifying your strategic goals and operational needs will help you determine the terms of any license.
• It is important for both the licensor and licensee to carry out due diligence before entering the negotiation of a license transaction. The licensor will want to be confident that the license is likely able to perform its financial and operational obligations under the license. The licensee will want. assurances that the licensor has the legal right to license the technology and as to the status of any patents or encumbrances on the intellectual property.
• Research other companies that have partnered with your potential licensee/licensor and what their experience was. Review your potential partner’s experience in developing and commercializing products in the relevant industry, and check to see if it has been involved in any disputes.
• Discuss the clear goals of each party and define the basic terms upon which both parties agree. Some of the key terms of a license include the scope of the license (field of use, territory, breadth of the licensed intellectual property, exclusivity), diligence requirements of the licensee, control of IP (ownership, prosecution, enforcement), and the financial terms (upfront payments, milestones, royalties).

For more information on the work that Torys does to support life science companies, reach out to our team.

AI Trends in 2022

AI is advancing at full pace with groundbreaking changes appearing every few weeks. The field is advancing so alarmingly that many practitioners are calling for ethical AI controls to be in place to govern the creation of AI. In many ways current AI techniques surpass our wildest dreams in their ability to create and innovate. Yet limitations still exist. Although advances toward “General AI” are being made, human-level AI is probably another decade from reality. But a decade is not a long time. Imagine a reality in which machines can do anything that people do.

The field of AI has seen exciting changes over the last few years with the discovery that pre-trained large language models are effective at solving complex AI problems. While standard research continues with incremental advances in various areas, most of the attention and press has been devoted to major advancements in language understanding, image understanding, language generation, and image generation. Also, of note is that language understanding and generation for non-natural languages, like programming languages, has also seen major advances due to large language model developments.

Most people tracking AI over the years are familiar with the rise of machine learning and search, the two branches of research that divide AI. While Machine Learning (ML) covers the fields of artificial neural nets, reinforcement learning and other forms of statistical learning, search covers automated reasoning, game playing, logic programming, constraint reasoning, theorem proving, and other symbolic manipulation concepts. Advances in machine learning have dominated news recently with the development of generative models that can make up anything that requires intelligence. This includes language, poetry, art, music, software and much more.

I’ve curated some of the more interesting developments in AI.

Transformer Based Large Language Models

At one point in time, full language comprehension was thought to require vast databases of carefully curated knowledge. Large language models do not require this type of effort. The architecture and size of LLMs are powerful enough to allow training alone to be used on a vast database of books, articles, websites and more. GPT-3 from OpenAI was the first large language model to significantly alter the landscape of language-based AI. It is a huge system with over 175 Billion parameters making it one of the largest models ever deployed commercially.

Transformers rely on completely new AI concept called “Attention”. The concept of attention Is based on the idea that all inputs need to be compared directly with all other inputs in one operation. This idea works extremely well and is computationally very efficient on modern hardware such as graphical processors which are designed for highly parallel computation. Multiple layers of attention for highly abstracted version of input which are then decoded back into full sentence or into images.

The impact of transformers on language and image processing has been dramatic. A GPT-3 generated paragraph or article is so good, it is usually indistinguishable from human writing. While not fully “General AI”, GPT-3 seems like its getting closer to that point. 

Low code and No-Code Intelligence

One of the applications of GPT-3 is code understanding and code generation. OpenAI has created a version of GPT-3 that they refer to as “Codex”. Codex is now integrated into 70 different platforms and is used for code generation and code completion.

Image Generation

A few years ago, the concept of Generative Adversarial Networks was introduced, and it was ground-breaking. The concept incorporated one neural network to generate images and another one to critique the images. The generated images were incredibly realistic. You can check out examples on “Thispersondoesnotexist.com”. The site generates faces that are so realistic it is impossible to tell that they are made by an AI system. Since then many variants of GAN have emerged to generate any type of image you can imagine.

More recently OpenAI released DALLE 2, a transformer-based image generator that combines the power of language processing with the power of image processing. A user can provide any phrase describing a scene, whether it is realistic or fantasy, and DALLE 2 will build a full image publication ready. DALLE 2 generates incredibly interesting, one-of-a-kind artwork in response to any user query.

Hybrid AI and General AI

With the advent of almost human AI the limitations of neural network based AI systems are starting to emerge. GPT-3 for example can understand many concepts, but is unable to do math, process dates, or think deeply about anything that requires a systematic and logical thought process. The thinking of GPT-3 is intelligent but limited in depth.

The solution to neural net limitations is to integrate logic processing within lower layers of the network. This mechanism is referred to as Neurosymbolic processing and it will have a major impact on neural nets in the coming years. Neurosymbolic processing will enable complete generalized AI to emerge that can both process language and images as well as think logically.

Game Play

Game playing systems are one of the more interesting applications of AI to emerge in recent years. The ancient game of GO was once thought to be impossible for computers to beat humans. A team of AI scientist put Reinforcement Learning together with Neural Networks and a game playing algorithm to build a hybrid system that can win any GO game against any human. Since that time DeepMind has built game playing systems for all the major games. Related techniques have even been applied to poker; another game that was once thought impossible to beat humans.

Folding Proteins

Folding proteins is a practical application, beyond games, for the Deepmind GO method. The GO team realized that the process of finding viable protein folding configurations was similar to the search techniques used in game playing. Protein folding using Deepmind and other related models has revolutionized the field of biology and medicine, providing accurate predictions of the three-dimensional structures of proteins.

The ability to accurately predict the three-dimensional structure of a protein from its amino acid sequence is of great importance in biology and medicine. Proteins are the molecules that carry out the majority of the biochemical functions in cells, and their three-dimensional structures are crucial for their function.

Many diseases are caused by proteins with abnormal structures and understanding the three-dimensional structure of proteins is essential for designing drugs that target specific proteins. Traditionally, the three-dimensional structures of proteins have been determined experimentally, using techniques such as x-ray crystallography and nuclear magnetic resonance spectroscopy. However, these techniques are expensive and time-consuming, and they can only be used to determine the structures of relatively small proteins. In recent years, computational methods have been developed that can predict the three-dimensional structures of proteins from their amino acid sequences. These methods are much faster and less expensive than experimental methods, and they can be used to predict the structures of very large proteins.

Autonomous Vehicles

AI is the essential technology enabling autonomous vehicles to drive themselves. In the US 38 states have enacted laws to enable autonomous vehicles. In China, robotaxis are now in regular use in many cities. AI is used in autonomous vehicles to achieve situational awareness, the ability to understand one’s surroundings, and navigate and drive the vehicle accordingly. AI is also used to detect pedestrians, cyclists, and obstacles in the vehicle’s path. AI is used in autonomous vehicles to make decisions about when to change lanes, turn, and brake. In the future, AI will be used to enable cars to communicate with each other and with infrastructure such as traffic lights and road signs. This will allow cars to avoid accidents and improve traffic flow.

Accelerated AI Hardware

The rapid advancement in the applications of AI is, in part, due to the development of efficient algorithms that implement AI on specialized hardware. Nvidia, for example, is the world leader in Graphical Processing Unit hardware. Large neural nets run at accelerated rates on Nvidia cards. Training Deep learning nets is very expensive and time consuming. Accelerated neural networks can train at 10000s of times the speed of standard CPU based processes.

The Future

AI is one of the most important technologies of our time and will affect nearly every aspect of our lives in the coming years. Machines that can think like people, that can solve problems and replace human efforts will revolutionize business, commerce, medicine, engineering, education, and everything else. While current AI systems are limited to single purpose implementations, emerging “General” AI systems will soon integrate multiple forms of intelligence processing into one hybrid system that can think like a person.

A tremendous amount of innovation occurs in academia and the medical industry, where medical devices are conceptualized and developed to improve the lives of populations and produce favourable clinical and economic outcomes.Regulatory approval, reimbursement, and market adoption of medical devices involve a variety of stakeholders, each with unique requirements. All groups expect some degree of clinical and at times economic evidence (herein referred to as clinical evidence) to aid in their decision making.

The level and extent of clinical evidence (completed and published studies) required for regulatory clearance and approval of Medical Devices can vary based on factors such as the risk level and regulatory class of the device, existence of similar products with established safety and performance profiles on the market, and the nature of the disease state addressed by the device.

In the US for example, the FDA Premarket Approval process requires more rigorous clinical studies, while devices that are cleared through the 510k process can benefit to some extent from the published data on a predicate device. Minimally manipulated tissue products on the other hand are not considered medical devices and are bound to less stringent requirements.

For developers and manufacturers of medical devices, balancing the upfront cost and timeline of conducting clinical studies with the desire for speed to market, ramifications on market adoption and reimbursement are integral parts of the strategic planning during medical device development and commercialization.

As a Medical Affairs leader in charge of teams driving initiatives to foster safe and effective adoption of medical devices, I experienced first-hand the advantage of launching medical devices with robust published clinical evidence. That is, clinical studies of appropriate type and scope that clearly demonstrate the clinical and economic benefits of the medical device and meet the expectation of the stakeholders mentioned above. This is an attainable undertaking once it is planned well-based understanding of stakeholder needs and available types of studies and sources of data.

In contrast, running into objections or a slow adoption in the market and having to plan and execute studies in retrospect, leaning on data from other, similar technologies to support a newly introduced product, can decelerate the desired momentum of a device launch and slow down access of the patients to advanced therapies.

The strategy for evidence generation involves understanding the requirements and timelines of stakeholders and geographies, identifying gaps in existing evidence, selecting appropriate study types to generate the right level of evidence, designing studies, partnering with field experts, securing budgets, selecting journals for publication, and specifying appropriate forums for presenting the data.

Different mechanisms for creating clinical evidence include company-sponsored studies, investigator- initiated studies, and mining real world evidence databases. Types of clinical studies include phase I-IV studies, randomized clinical trials (RCT) to case series, and prospective and retrospective studies collecting clinical and economic data. Also, secondary analysis of existing data sets, systematic reviews, and meta-analysis of published literature can help establish the safety, efficacy, and economic outcomes of medical devices.

Educational and marketing communications should be founded on evidence-based scientific platforms. Equally important as evidence generation, is the communication of such evidence to demonstrate clinical and economic outcomes of the devices via (ideally open access) publications, conference presentations, medical education, and peer-to-peer discussions.

In the absence of such a foundation, many innovative products have failed in the marketplace, depriving patients of the benefits and the companies of the successes they would have experienced.

Evidence generation, medical communication, and evidence-based scientific platform for medical devices are within the expertise of Exquisite Biomedical Consulting.

Exquisite Biomedical Consulting (EBC) is a boutique-style medical affairs consulting firm based inVancouver, BC, Canada with roots in San Antonio, TX, USA. The company is led by Shabnam Vaezzadeh, MD, MPA, who has extensive experience in this field in corporate and consulting capacities. She is joined by expert clinicians, biostatisticians, and reimbursement professionals to best serve the Medical Affairs needs of funded medical device companies.

For more information, please refer to:

Company: Exquisite Biomedical Consulting Ltd

Shabnam Vaezzadeh, MD, MPA, BCMAS, CEO

Email: contact@exquisitebiomedical.com

Website: https://exquisitebiomedical.com

LinkedIn: https://www.linkedin.com/company/exquisite-biomedical-consulting

                                                                                           

                                                        

Torys’ Tips™: What you need to know about IP 

By Eileen McMahon and Karen Townsend 

As cross-border IP lawyers, we work with life science companies across the entire industry. We  guide clients through every aspect of intellectual property, such as creation, acquisition, and  the management and protection of IP rights. 

Unsurprisingly, how you structure your IP strategy will depend on various factors unique to  your organization and business plan, however, there are common considerations that each  company should keep in mind. 

• The first step to an IP Strategy at a small or medium-sized enterprise (SME) is to  determine the budget that you have for IP. What is the budget for this year? What is  the approximate budget for the next few years? These are data points that must be  factored into your IP strategy. 

• A sound IP strategy might include a decision to defer filing a patent (while maintaining  the confidentiality of an invention). Filing a patent for every innovation within your  company is a costly strategy and you want to ensure you are filing for inventions that  you expect will be valued by investors and competitors. 

• Remember any disclosure of your invention (e.g., at a conference, in an abstract, as part  of a Q&A in a business meeting) could harm you if the invention has not been covered in  a patent application. 

• Deal with any IP ownership issues early (e.g., get assignments executed as soon as the  patent is filed, or the branding is created). This will help keep your IP budget in check  down the road. 

• There are invariably pros and cons to each IP decision. The best you can do is to do your  homework and make a decision that is right for your company, based on the data points  available to you (including the IP budget). 

• There is a lot of information that is publicly available that can help inform your. decisions  on IP strategy. What patents are your competitors filing and in which countries? For the  “big players” in the therapeutic class you’re working in, look at what scope of patents  they are seeking and in which countries they are filing. All of this information is publicly  available and should be part of your homework. 

For more information on the work Torys does to support life science companies, reach out  to our team. 

Eileen McMahon is a co-founder of the intellectual property and food and drug regulatory  practices at Torys. She represents the entire spectrum of companies on regulatory clearance  and intellectual property protection of products. Across sectors—including life sciences  (pharmaceuticals, medical devices, natural health products), agribusiness, consumer products  and more—Eileen helps clients identify, protect and leverage IP and regulatory assets, obtain  and maintain market exclusivity, handle high-risk situations (corrective actions, recalls, regulatory orders), and navigate the impact of current and proposed laws on clients’ ability to sell products. Eileen also has market-leading experience with patented medicines and the oversight of Canada’s Patented Medicines Prices Review Board (PMPRB). Eileen also represents investors and companies looking to finance or invest in companies with intellectual property  and regulatory assets, as well as companies looking to acquire or divest such assets. 

Karen Townsend has extensive experience advising clients on pharmaceuticals, biotechnology,  food and drug law and intellectual property issues. She brings deep technical skills to clients’  work in therapeutics, molecular biology, immunology, regenerative medicine, personalized and  precision medicine, vaccines, and drug delivery systems, making her go-to counsel for patent  protection issues of all kinds. 

Karen has substantial experience in all aspects of patents, including drafting and prosecution,  and regulatory issues relating to acquiring, maintaining, and defending patent rights. She also  provides advice on risk management of intellectual property and regulatory matters. For  investors interested in life science companies, Karen assists in evaluating technologies and  intellectual property portfolios. 

Karen is a registered patent agent in the United States and Canada. Having worked in the  United States previously, Karen is one of a handful of patent agents residing in Canada who has  passed both the U.S. and Canadian patent agent exams and is allowed to represent any  applicant before the United States Patent and Trademark Office and the Canadian Intellectual  Property Office.

Live from Canada: The Future of Biomanufacturing

Tuesday, April 12, 2022 | 1 - 2 PM EST

Attend Live from Hamilton, Ontario or Watch via Livestream

Dear CELS

We’re very excited to introduce you to an important Canadian Life Science industry event: “Live from Canada: The Future of Biomanufacturing” at McMaster Innovation Park in Hamilton, Ontario.

Eric Burak, CSO Fusion Pharmaceuticals will be the key note speaker and the moderator will be Anne Woods, Managing Director - Life Sciences and Healthcare,  Silicon Valley Bank Canada.

This program will discuss Canada’s renewed commitment to biomanufacturing and why it is a great option for companies interested in building or expanding.

At this event, you’ll learn about the plans for biomanufacturing development in Hamilton with a case study of a cross-border company that has successfully implemented this strategy.

You may attend this event in-person from Hamilton, Ontario or watch via Livestream. This event is free and open to the public but registration is required.

Registration links will take you to CENE, US host of the event.

Register - Livestream

Register - Attend Event in Person

Wednesday December 08 / 3:30 - 5:00 PM (Eastern Time)

From CELS East Coast ally: CENE

Come meet the 11 exciting Canadian companies who are ready to celebrate their graduation from the Boston CTA 2021 program with lots of great innovation revolutionizing the world of healthcare, fintech and cybersecurity, sportstech, robotics, and many others. Let’s meet the entrepreneurs, have fun, and raise a glass to Canada!

Free, Virtual Event

Register Here

Featured Companies:

1. Advanced Intelligent Systems– Zero-emission autonomous robotic vehicles for agriculture and healthcare
2. Affinite Instruments– Novel immunoassay therapy for diagnostics and bioproduction
3. Axolotl Biosciences– Reagents, tissue models, and consulting services for 3D bioprinting
4. FactR– Enterprise transaction management platform, built on Smart Contracts for accuracy and security
5. Fluid Biotech– Flow-diverting dissolvable stent for brain aneurysms
6. IPtoki– Digital identity validation using behavioral biometrics, AI and blockchain
7. LynX Inspection– Industrial inspection solutions based on a novel 3D radiographic method
8. OPTT– Digital mental health providing validated digital care plans to healthcare organizations
9. Pegasus Imagery– Unmanned aircraft / sensor systems for autonomous data collection at scale
10. Xesto– Computer vision AI, at home sizing tool for feet, hands, faces

Dear CELS members,

If you are in the Bay Area over the Canadian Thanksgiving weekend and fear missing out on a great turkey dinner, consider joining local Canadian expats at the annual Digital Moose Lounge / UC Berkeley Canadian Studies on the Berkeley campus.

Details at the link below 

RSVP

Stanford Byers Center for Biodesign and Fogarty Innovation

Together with MDMA, WSGR, AdvaMed, Medtech Strategist and SVB,

are pleased to present:

The American Medical Association webinar

CPT® CODES and INNOVATION

Physician innovators help drive the future of medicine by solving problems and improving patient care. One of the keys to a successful invention is understanding how a new device or procedure fits into the Current Procedural Terminology (CPT) code landscape.

This free webinar will help you understand how the codes used by physicians, health plans, and health technology companies to describe care also support innovation.

Specifically, you will learn how the CPT process works, how to engage with the CPT editorial panel, and when to apply for a new code.

More Info & Register