Category: General

Triomics secures $15M in Series A funding to streamline cancer trial participant matching.

In the complex landscape of cancer treatment, clinical trials represent a beacon of hope, offering new therapies that could potentially extend or even save lives. Despite this, the rate of enrollment in these trials remains startlingly low, with only 3% to 5% of eligible patients participating annually in the United States. The reasons behind this are multifaceted, but a significant barrier has been the time-intensive process required for medical professionals to match patients with appropriate trials. This is where Triomics, a generative AI startup, steps in with a promise to transform this critical aspect of cancer care.

The Challenge of Clinical Trial Enrollment

Clinical trials are crucial for the development of new cancer treatments. They offer patients access to cutting-edge therapies that are not yet available on the market. However, the enrollment process is fraught with challenges. One major hurdle is the sheer amount of time it takes for oncologists and nurses to identify suitable trials for their patients. These medical professionals are often overwhelmed by their day-to-day responsibilities and struggle to keep up with the vast array of ongoing clinical trials.

The task of matching a patient with a trial is not straightforward. Most trials have stringent eligibility criteria, including the stage of cancer, specific mutations, and prior treatments the patient has undergone. Reviewing these factors against a patient’s medical records to find a suitable trial is a time-consuming process, often requiring several hours of meticulous work.

Personal Stories Highlight the Struggle

The difficulties of finding the right clinical trials are not just statistics—they affect real people. Many individuals, like myself, have experienced the challenge firsthand while trying to find trials for loved ones. I spent countless hours navigating to find options for my father and, more recently, for a friend with stage IV cancer. In many cases, doctors may only suggest one trial, if any, leaving patients and their families to do their own research for additional options.

Triomics: A New Hope with AI

Founded by Sarim Khan, a former MIT biotech researcher, and Hrituraj Singh, an AI scientist previously with Adobe, Triomics aims to tackle these issues head-on. The duo, friends since their college days, launched the startup in 2021 after recognizing how advances in generative AI and large language models (LLMs) could revolutionize the process of trial matching.

Triomics developed a specialized LLM, OncoLLM, designed to integrate seamlessly with the electronic health records (EHR) systems used by cancer centers and oncology departments. This AI-driven tool can rapidly parse through a patient’s medical history and match them with suitable clinical trials in minutes—a task that previously took several hours.

Table: Impact of OncoLLM on Clinical Trial Matching

Feature Before OncoLLM With OncoLLM
Time to Match a Patient Several hours Minutes
Number of Trials Considered Limited Extensive
Personalization of Matches Low High
Accessibility of Trial Matches Poor Improved

Expanding Impact and Market Growth

Since its inception, Triomics has seen significant adoption of its technology. Six cancer centers and hospitals are currently using or piloting OncoLLM, with plans to double this number by the end of the year. This expansion has been supported by a robust $15 million Series A funding round from prominent investors including Lightspeed, Nexus Venture Partners, General Catalyst, and Y Combinator.

Triomics is not merely a clinical trials company. The data processed by OncoLLM can also assist medical staff in preparing for patient visits and submitting detailed cancer progression reports to state regulatory agencies. The potential applications of Triomics’ technology extend beyond just clinical trials, touching various aspects of oncological care.

Competing in a Crowded Field

Triomics is not alone in the AI-driven clinical trial matching space. Other startups like Deep 6 AI, QuantHealth, and Trajectory are also developing technologies to improve the efficiency and effectiveness of trial matching. However, Khan believes that Triomics sets itself apart by processing extensive datasets specifically tailored for cancer centers.

Key Points

  • Low Enrollment Rates: Despite the availability of numerous clinical trials, enrollment rates among eligible cancer patients remain low.
  • Time Constraints: Oncologists and medical staff face significant time constraints, making it difficult to stay informed about available trials.
  • AI Solutions: Triomics utilizes generative AI to dramatically reduce the time required to match patients with clinical trials.
  • Broader Applications: Beyond trial matching, Triomics’ technology helps in preparing for patient visits and regulatory reporting.

In conclusion, Triomics represents a significant step forward in leveraging AI to address long-standing inefficiencies in clinical trial enrollment. By reducing the time and effort required to match patients with trials, Triomics not only enhances the accessibility of potentially life-saving treatments but also paves the way for a more responsive and patient-centric approach to cancer care.

Fintech disputes have led TabaPay to abandon its purchase of bankrupt Synapse.

In a significant shift in the fintech landscape, TabaPay has officially withdrawn its intent to acquire the assets of the financially troubled Synapse, a banking-as-a-service startup. This decision, confirmed through multiple sources including TechCrunch and statements directly from the involved companies, highlights a complex web of relationships and contractual disagreements, primarily involving another key player, Evolve Bank & Trust.

Key Points of the Dispute

  • TabaPay Withdrawal: The instant payments company has terminated its agreement to purchase Synapse, citing unmet conditions.
  • Synapse’s Challenges: Facing bankruptcy, Synapse alleges complications involving its banking partner, Evolve, which they claim failed to meet crucial financial obligations.
  • Evolve’s Response: Evolve Bank & Trust denies involvement in the conditions causing the deal’s collapse and asserts it has fulfilled its own financial commitments.
  • Mercury’s Position: Mercury has dismissed Synapse’s accusations as baseless, maintaining that all financial transitions and customer funds are properly accounted.

Chronology of a Failed Acquisition The roots of this acquisition’s failure stretch back to the initial announcement on April 22, when both Synapse and TabaPay suggested that a merger was pending bankruptcy court approval, with a surprisingly low purchase price of $9.7 million compared to the $50 million Synapse had raised in venture funding. However, the deal faced immediate hurdles, outlined in detailed communications and court statements:

  1. Bankruptcy Court Declaration: Synapse’s legal team revealed during a bankruptcy court session last Thursday that the planned acquisition would not proceed.
  2. Official Confirmation: By Thursday afternoon, a TabaPay spokesperson had confirmed to TechCrunch that the company had issued a “termination notice of the purchase agreement” that morning due to failure in meeting the deal’s closure conditions.
  3. Evolve’s Alleged Non-compliance: Synapse’s CEO, Sankaet Pathak, asserts that the deal could still be viable if Evolve Bank & Trust fulfilled specific funding obligations for ‘For Benefit Of’ (FBO) accounts, a claim Evolve disputes.

Detailed Breakdown of the FBO Account Issue FBO accounts, crucial for managing third-party funds, lie at the heart of the disagreement. Pathak claims that despite assurances, Evolve failed to fund these accounts adequately, a necessary condition for completing the TabaPay acquisition. Evolve, however, maintains that it was not responsible for the deal’s conditions, although it had a separate settlement agreement with Synapse requiring fund provision, which it claims to have satisfied.

Mercury’s Involvement and Dispute The saga also involves Mercury, a business banking startup and another banking partner to Synapse. Following a breakdown in their working relationship with Synapse, Mercury and Evolve decided to directly collaborate, sidelining Synapse. Pathak’s statements in a Medium post suggest that this move was detrimental to Synapse’s operational and financial health, particularly when Mercury allegedly withdrew $49.6 million more than was due from Synapse-affiliated accounts. Mercury, for its part, claims that the transition was seamless and denies any financial mismanagement.

Impact and Future Implications This aborted acquisition not only affects the immediate parties but also casts a shadow over their reputational and operational capacities. It raises questions about the robustness of contractual agreements and the responsibilities of banking partners in facilitating or derailing significant financial transactions in the tech industry.

Table: Financial and Operational Milestones in Synapse’s History

Year Event
2014 Founding of Synapse
2017 Peak venture capital raised ($50M)
2022 First layoffs announced (18% of workforce)
2023 Additional layoffs (40% of workforce)
2024 Filed for Chapter 11 bankruptcy

Moving Forward As the dust settles on this failed deal, the focus for Synapse remains on navigating its bankruptcy proceedings and seeking other potential rescuers or strategic directions. For TabaPay, this might mean reevaluating its acquisition strategies, particularly how it engages with banking partners in future deals. Meanwhile, the tech and financial sectors will likely watch closely how Evolve and Mercury manage the fallout and maintain their business operations amidst public scrutiny and legal challenges.

Perplexity has recently partnered with SoundHound to enhance its voice assistant technology.

As the artificial intelligence landscape continues to evolve, two notable companies are making significant strides. OpenAI is in the process of launching a search-oriented product poised to challenge tech giants like Google and Bing. Meanwhile, Perplexity, a burgeoning force in the AI industry, is enhancing its market presence through strategic partnerships and a focus on global expansion.

The Rise of Perplexity

Founded by Aravind Srinivas, Perplexity has rapidly gained attention with its AI-first approach to knowledge engines. Recent weeks saw the company disclose plans for global expansion, particularly through partnerships with major telecommunications firms. The latest development in its expansion strategy involves a collaboration with SoundHound, a leader in voice AI technology.

This partnership, announced just yesterday, is set to integrate Perplexity’s advanced large language model (LLM)-driven capabilities into SoundHound’s Chat AI voice assistant. This move is expected to enhance user experience significantly by making the voice assistant more adept and responsive than ever before.

Dmitry Shevelenko, the Chief Business Officer at Perplexity, emphasized the impact of this integration: “Through this partnership, we’re one step closer to our goal of making Perplexity available on every device. With voice AI’s rising popularity, this makes accessing needed information easier and more intuitive for users everywhere.”

What This Means for SoundHound and Its Users

SoundHound, established over a decade ago, has been at the forefront of speech recognition and voice AI solutions across various industries. Its Chat AI, akin to Siri, allows users to engage in dialogue and obtain straightforward answers. It pulls real-time data on numerous topics like weather, sports, and restaurants, and synthesizes this with static large language models to deliver comprehensive responses.

The integration of Perplexity’s online LLMs with Chat AI marks a significant enhancement. These models, which inherently surf the web to pull the most current and useful information, will allow Chat AI to address even more complex, time-sensitive questions than before.

For example, a user could ask, “How does this week’s gas price compare to last week?” The enhanced Chat AI would provide an accurate, live update on gas prices and a detailed comparison with the previous week. This query could be followed by a command like, “Navigate to the nearest gas station,” to which SoundHound would seamlessly provide directions using the most relevant data.

The Technical Edge: Perplexity’s LLM Options

Perplexity currently offers two sizes of its online LLMs: pplx-7b-online and pplx-70b-online. While SoundHound has not specified which models it will employ, the capabilities these models bring to the table are significant.

Table: Comparison of Perplexity’s LLM Models

Model Capabilities
pplx-7b-online Suitable for basic queries, efficient in processing speed
pplx-70b-online Advanced processing, handles complex queries more adeptly

Future of Voice Assistants

With the integration of Perplexity’s search capabilities, SoundHound’s Chat AI is positioned to become a top contender in the realm of generative AI-powered voice assistants, rivalling Google Assistant and Alexa. This technology is already deployed in over 12 countries and supports 18 languages with Stellantis in the automotive sector.

Mike Zagorsek, COO of SoundHound AI, shared his enthusiasm: “By integrating these advanced search capabilities, we are not only enhancing the functional range of our voice assistants but also improving user engagement. As more people opt for voice interactions over typing, we anticipate a significant uptick in usage.”

Industry Impact and Consumer Trends

Both Google and Amazon have announced plans to upgrade their voice assistants with generative AI models, although these enhancements have not yet been rolled out globally. Apple is also expected to introduce an improved AI-driven version of Siri.

Key Takeaways:

  • Strategic Partnerships: Perplexity’s collaboration with SoundHound extends its reach and enhances its market presence.
  • Enhanced Capabilities: The integration with SoundHound’s voice AI will allow more complex and timely queries to be handled efficiently.
  • Broader Impact: This partnership signals a shift towards more dynamic, conversational capabilities in voice AI technology.

As AI technology advances, the implications for everyday technology use are profound. Perplexity’s strategic movements, especially its partnership with SoundHound, not only expand its operational horizons but also redefine how we interact with devices in our interconnected world.

Neurable Secures $13M in Funding to Integrate Brain-Computer Interfaces with Daily Use Products

In a significant advancement for brain-computer interface (BCI) technology, Neurable, a Boston-based neurotechnology firm, has successfully raised $13 million in a recent funding round. This injection of capital is aimed at accelerating the development and commercialization of Neurable’s groundbreaking BCI AI technology across various industries.

Transforming Neurotechnology

The funding round saw participation from several prominent venture capital firms including Ultratech Capital Partners, TRAC, Pace Ventures, and Metaplanet, highlighting the growing investor interest in innovative neurotechnologies. Since its inception, Neurable has raised over $30 million, demonstrating strong support for its vision to make BCI technology a staple in everyday products.

Funding Overview:

  • Total Raised to Date: $30 million+
  • Recent Funding: $13 million
  • Key Investors: Ultratech Capital Partners, TRAC, Pace Ventures, Metaplanet

Neurable’s mission is to democratize access to advanced neurotechnology. The company plans to use the latest funds to expand its platform technology and scale its licensing business. This strategic move is expected to catalyze further development and experimentation in a variety of applications, making BCI technology more accessible to consumer audiences.

Strategic Objectives Post-Funding:

  • Advance Platform Technology: Enhance the core technology for broader applications.
  • Scale Licensing Business: Expand partnerships across multiple industries.
  • Broaden Consumer Reach: Make non-invasive BCI technology widely available.

The company’s CEO, Ramses Alcaide, expressed his enthusiasm about the funding, stating, “This new round of funding underscores our commitment to making Neurable’s brain-computer interface technology accessible to everyone. We’re empowering individuals to understand their own mind, optimize human performance, and conquer the most pressing health challenges of our generation.”

Product and Platform Expansion

With the fresh capital, Neurable intends to continue expanding its platform, which provides companies and original equipment manufacturers (OEMs) access to its non-invasive BCI technology. This includes expanding its product portfolio, reference designs, algorithms, and enabled systems to encompass a wider range of products such as earbuds, helmets, and various head-worn devices designed to optimize human performance.

Key Products and Technologies:

  • MW75 Neuro Headphones: AI-powered BCI-enabled headphones set to launch this summer.
  • EEG AI Technology: Compact and powerful technology optimized for everyday use.
  • Enabled Systems: Expansion to include earbuds, helmets, and other head-worn devices.

Dale Davis, a senior principal at Ultratech Capital Partners, emphasized the potential of Neurable’s technology, remarking, “Neurable’s transformative neurotechnology is at the forefront of the BCI revolution. BCI technology has gained significant momentum over the years, and its advancement shows no signs of slowing down. Neurable’s BCI has the potential to solve a range of vexing issues — from healthcare to daily life. BCI integrated into our devices, and a critical part of our everyday experience was once the stuff of science fiction — thanks to Neurable, that dream will soon be a reality.”

Collaborative Efforts and Future Aspirations

Founded as a University of Michigan spinout, Neurable has continually sought to collaborate with leading entities in both the private and public sectors. Following its Series A funding in 2020, Neurable partnered with consumer wearable companies, including headphone company Master & Dynamic, to embed EEG sensors into everyday technologies.

The partnership is set to introduce the first-ever BCI-enabled headphones, the MW75 Neuro, marking a significant milestone in consumer-accessible neurotechnology. Additionally, following Series A, Neurable collaborated with the Air Force Research Lab’s 711 Human-Performance Wing to validate and refine its technology for enhancing human performance.

Building on this successful collaboration, Neurable secured $5 million in contracts from the Department of Defense to further develop this cutting-edge human technology to support soldier health and performance.

Adam Molnar, cofounder and vice president of strategic partnerships at Neurable, shared his excitement about the partnerships, stating, “We’re extremely proud to work with our partners, which include some of the world’s best in consumer technology like Master & Dynamic as well as the very servicemen and women who make sacrifices on a daily basis for the overall security of our nation. This is just the beginning. We can’t wait to show you what’s coming next.”

As Neurable continues to push the boundaries of what is possible with neurotechnology, its recent funding round not only validates its past achievements but also sets the stage for an exciting future of innovation and widespread application of BCI technology.

Espresso AI debuts with $11M in funding to address rising cloud expenses.

Espresso AI, a Silicon Valley-based artificial intelligence startup, recently emerged from stealth mode, announcing that it has successfully raised over $11 million in seed funding. This substantial financial backing aims to address one of the most pressing challenges in enterprise computing: controlling spiraling cloud costs.

Funding and Support from Industry Leaders

The funding rounds include a seed round led by prominent investors Daniel Gross and Nat Friedman, complemented by a pre-seed round spearheaded by Matt Turck at FirstMark. These rounds also saw participation from a cohort of industry leaders, signaling robust confidence in Espresso AI’s potential to revolutionize cloud cost management.

Innovative Technology to Slash Cloud Costs

At the core of Espresso AI’s innovative approach is its groundbreaking technology, leveraging advanced language models and machine learning to automate code optimization. This technology is specifically designed to reduce cloud compute costs by up to 80%. Initially, the company has focused on optimizing SQL queries for Snowflake, a leading cloud data warehousing platform.

Ben Lerner, the founder and CEO of Espresso AI, in an exclusive interview with VentureBeat, highlighted the vast potential of their solution. “Snowflake alone has $2 billion in annual revenue. Across the broader data warehousing landscape, we see potential revenue in the hundreds of millions for us and billions in possible savings for our customers,” Lerner explained.

The Growing Crisis in Cloud Costs

As more enterprises move to cloud platforms, they encounter new challenges related to cost control and visibility. This transition has often resulted in unexpectedly high bills and difficulties in forecasting and managing expenditures. Data warehousing has become particularly problematic, as it consumes significant cloud resources, and optimizing these workloads for cost and performance has been notoriously difficult.

During discussions, Lerner emphasized, “Users consistently mention Snowflake as their second largest expense following AWS. At Snowflake events, the focus is heavily on cost and performance.”

Table: Financial Overview of Espresso AI’s Seed Funding

Participant Role in Funding Contribution
Daniel Gross Lead Investor (Seed Round) Major Contributor
Nat Friedman Lead Investor (Seed Round) Major Contributor
Matt Turck Lead Investor (Pre-Seed Round) Major Contributor
Industry Leaders Participants Significant Contributions

AI-Driven Solutions for Code Optimization

Espresso AI’s strategy involves utilizing large language models (LLMs), foundational technology behind phenomena such as ChatGPT, to tackle code optimization challenges. These models are trained to deeply understand SQL queries and database architectures, enabling the platform to automatically refactor queries for enhanced efficiency.

The process involves continuous analysis of queries executed against the data warehouse, identifying optimization opportunities through a blend of natural language processing, program synthesis, and reinforcement learning. The technology then rewrites queries on-the-fly, enhancing performance and minimizing compute usage.

Lerner notes the power of automation in this domain: “The strength here is that unlike traditional applications requiring manual checks for accuracy, our optimized code is automatically verified for correctness, focusing solely on speed enhancement.”

Simplified Integration and Future Plans

Setting up Espresso AI is designed to be straightforward, operational in under 10 minutes by altering a single connection string. “It’s as easy as changing a URL,” Lerner said. “You simply redirect your BI and analytics tools to our endpoint instead of directly to Snowflake, and we manage the rest.”

Bullet Points: Key Features and Benefits of Espresso AI

  • Advanced AI Technology: Utilizes LLMs for deep learning and understanding of database queries.
  • Significant Cost Reduction: Capable of cutting cloud compute costs by up to 80%.
  • Easy Setup: Integration in less than 10 minutes with minimal configuration.
  • Continuous Optimization: Automatically refactors queries to improve efficiency.
  • Scalability: Initially compatible with Snowflake, with plans to extend to other SQL data warehouses like Databricks.

Looking ahead, Espresso AI is poised for rapid growth, planning to use its funding to accelerate product development and market entry strategies. While the initial focus remains on Snowflake, the company’s roadmap includes expanding its AI optimization engine to cover additional SQL data warehouses and eventually broader computing needs.

As the computing world contends with financial constraints and the demand for digital transformation, technologies like those offered by Espresso AI that deliver substantial cost savings without compromising performance will undoubtedly attract significant attention from CIOs and IT leaders. If successful, Espresso AI could redefine efficiency in cloud computing, making it as essential as a morning cup of coffee for IT departments everywhere.

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