Artificial Intelligence
Basecamp Research Launches BaseFold: A Breakthrough in 3D Protein Structure Prediction of Large, Complex Protein Structures
BaseFold leverages Basecamp Research’s purpose-built foundational dataset to significantly increase prediction accuracy of large, complex protein structures and small molecule interactions — it is up to six times more accurate than AlphaFold2 and offers up to a three-fold improvement in small molecule docking
More reliable 3D structure predictions for larger and more complex proteins is poised to greatly accelerate AI-based drug discovery efforts
LONDON, March 12, 2024 /PRNewswire/ — Basecamp Research, a world leader in artificial intelligence (AI)-based design of proteins and other biological systems, today announced the launch of BaseFold, its new deep learning model that predicts 3D structures of large, complex proteins more accurately than other AI-powered tools, including the industry gold standard, AlphaFold2. These data were recently published in bioRxiv.
BaseFold was created by augmenting the AlphaFold2 model, which predicts the 3D structure of a protein based on its amino acid sequence, with BaseGraph. BaseGraph is Basecamp Research’s purpose-built foundational dataset for biological AI, collected via access and benefit-sharing partnerships with over 25 biodiversity-rich countries. The published accuracy improvements are just a starting point, as BaseFold is continuously improving week over week as Basecamp Research scales its global network of biodiversity partnerships. Furthermore, Basecamp Research will be working with NVIDIA to optimise and productionise BaseFold for NVIDIA BioNeMo, a generative AI platform for drug discovery.
The scientific benchmark for determining protein structure is still via slow and time-consuming experimental methods such as X-ray crystallography. However, AlphaFold2’s development in 2020 provided a breakthrough for the use of AI across biotechnology, giving scientists confidence in AI-based structural predictions. A wide array of structure prediction models have since followed AlphaFold2, most notably CollabFold, ESMFold, OpenFold and RoseTTAFold.
However, the performance of these models is highly dependent on their training data; all are trained on public protein databases that are widely seen as unfit for biotech’s AI era. These public training datasets are small, unreliable and heavily biased toward proteins from laboratory model organisms. The sequence data captured in these public databases is estimated to represent less than 0.000001% of life on Earth. These data limitations mean that existing AI tools work well for predicting the structures of smaller, simpler proteins that are well-represented in public datasets but often struggle beyond that, creating major problems for those using AI to develop complex new medicines.
AlphaFold2 draws heavily from the public MGnify database, known for having issues with incomplete sequences, which can impact the quality of structures predicted for larger proteins. Basecamp Research’s BaseFold tackles the next big computational challenge, which is to achieve crystallography-level accuracy for larger, more complex proteins, especially those underrepresented in existing protein sequence databases.
To do this, BaseFold extracts orders of magnitude more meaningful evolutionary information from over 6 billion relationships in BaseGraph. Replete with extensive genomic context and comprehensive metadata, training algorithms on BaseGraph has been shown to yield significant advances in the performance of a wide range of biological AI models, including AlphaFold2 as presented here.
In this preprint, Basecamp Research scientists evaluated BaseFold’s performance in predicting the structure of various proteins selected from the CASP15 (Critical Assessment of Structure Prediction) competition and CAMEO (Continuous Automated Model EvaluatiOn) community project.
Publication Result Highlights
Basecamp Research’s purpose-built foundational dataset allowed BaseFold to improve the accuracy of AlphaFold2’s predicted structures by up to 6-fold.The team demonstrated an up to 3-fold improvement in modelling accuracy for small molecule interactions with protein targets.BaseFold unlocks more reliable 3D structure predictions and small molecule docking for larger and more complex proteins than ever before, particularly those that are underrepresented in public datasets.This step change is poised to greatly accelerate drug discovery efforts, where understanding these interactions will allow for more advanced therapeutics molecules to be developed using AI.”We have redesigned and rebuilt the entire data acquisition process, making us the first team ever to collect and annotate biodiversity data with the same quality as human clinical genetic data — all purpose-built for the AI era,” said Dr. Phil Lorenz, CTO of Basecamp Research. “BaseGraph, the most diverse and comprehensive dataset of its kind, is the core driver of our advances in AI. The results of this publication prove that more diverse, representative genomics data allows for step-change algorithm improvements without the need for extensive lab-in-the-loop infrastructure. Our database is growing every week, and as a result, BaseFold is improving every week, too.”
“AlphaFold is one of the most useful AI tools in drug discovery, and for good reason. It enables researchers to better predict how medicines may interact with proteins in the body, shaving off years of work. However, AlphaFold still has significant room for improvement – particularly when being used to predict large, complex and underrepresented proteins, which are often the most critical for the development of new therapeutics. Even just a few percentage points of error can have major implications in accurately predicting protein-molecule interactions,” said Dr. Glen Gowers, co-founder of Basecamp Research.
“We know that when it comes to AI, the best data produces the best outcomes, and it’s rewarding to know that the new, purpose-built foundational dataset that we have built is already having widespread implications for drug development and human health,” Dr. Gowers added. “We’re not stopping here, though – we are continuing to scale our biodiversity partnerships and apply this data advantage across more and more biological AI models.”
The full preprint can be found here: https://www.biorxiv.org/content/10.1101/2024.03.06.583325v1
About Basecamp Research
Basecamp Research is a market leader in mapping biodiversity for AI-based design of biological systems. We match and refine novel proteins for our partners’ exact industrial, therapeutic or diagnostic applications using BaseGraph™, a new generation of AI design that is powered by the first-ever high-resolution map of global genetic biodiversity.
Understanding the full genetic, evolutionary, and environmental context of each protein allows Basecamp Research to design tailored proteins for specific applications without the need for expensive and time-consuming directed evolution campaigns. We’re a team of explorers, scientists and policy experts driven by our ambition to protect and learn from nature’s diversity, whilst delivering life-changing breakthroughs to those who need them most.
For more information, visit www.basecamp-research.com.
For media and other inquiries, please contact [email protected], 07867 488769
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Artificial Intelligence
How AIoT shapes the future of mobility: Hikvision at ITS World Congress 2024
HANGZHOU, China, Sept. 27, 2024 /PRNewswire/ — Hikvision made a significant impact at the ITS World Congress in Dubai with its captivating theme, “Embrace AIoT for safer, smarter, and greener mobility.” Its booth became a hub of innovation, where visitors explored AIoT solutions that are reshaping the transportation landscape, sparking deep conversations on the future of urban mobility.
Road safety revolution: harnessing AIoT for secure transportation
Hikvision’s commitment to road safety was on full display at its booth through the impressive array of AIoT solutions designed to create secure and reliable traffic environments. The company’s technology provides 24/7 traffic monitoring, ensuring continuous oversight of motor vehicles, non-motorized vehicles, pedestrians and environmental factors. This comprehensive, real-time information collection enables traffic managers to prevent accidents and enhance road safety. Among the showcased products was the 20 MP IR ANPR Checkpoint Capture Unit, renowned for its high-definition capture capabilities, bolstering traffic safety measures.
A standout innovation was the integration of advanced radar and camera technologies, ensuring uninterrupted, comprehensive detection even in adverse weather conditions. The Radar-Video Fusion Incident Detection Cameras, featured prominently in the product experience area, enable early detection and warning of potential hazards. They are particularly effective in challenging situations such as curved roads, blind spots at intersections, and obstacles beyond visual range.
Attendees also engaged with onboard monitoring products on the simulated bus, including dome network cameras, which is designed to enhance passenger safety. Driving assistance products, such as the Driver Status Monitor (DSM), were demonstrated to mitigate unsafe driving behaviors and ensure safer journeys.
Urban mobility redefined: smart traffic innovations
In the realm of smarter mobility, Hikvision showcased its multidimensional sensing technology, which integrates visible light sensors, infrared sensors, radar, and sonar. This technology expands perception capabilities, significantly improving traffic management and situational awareness. The use of AI-powered comprehensive sensing elevates incident monitoring and violation detection to unprecedented levels of accuracy and efficiency.
A major attraction was the Radar-Video Fusion TandemVu PTZ Camera, which integrates millimeter-wave radar with high-resolution cameras for extensive traffic detection and data analysis. AI-based algorithms combine these two systems to enhance target information, detecting up to 16 types of incidents. This leads to the development of a large-scale fusion model that merges spatial physical data with image semantic information. The result is ultra-long-range perception, achieving over 95% accuracy in vehicle trajectory detection. This robust system improves traffic violation management and optimizes traffic flow, significantly enhancing road efficiency.
At the simulated bus station, visitors observed how AI-assisted people counting automated the collection of passenger flow statistics at peak stop hours and bus line frequency during busy periods. Paired with smart bus stop digital signage, the solution improves bus service quality, operational efficiency, passenger experience, and overall public transport effectiveness.
Sustainable transportation: leading the charge for greener cities
Hikvision’s commitment to sustainable urban mobility was evident through its innovative green wave technology and eco-friendly checkpoint solutions. Green wave technology efficiently manages traffic flow to reduce congestion and lower carbon emissions, aligning with global sustainability goals. Visitors were particularly impressed by a case study showcasing a green wave solution implemented in Zhoushan, China. Over a stretch of 21 kilometers and 34 intersections, this main road cut travel times by 50%.
The use of DarkFighterX technology in checkpoint cameras also received significant attention. This technology senses both visible and invisible light, resulting in more accurate and realistic images. It enhances traffic violation enforcement efficiency while minimizing the need for high ambient light levels, thus reducing light pollution. The 9M DarkfightX ANPR Checkpoint Camera exemplified this dedication to environmental stewardship.
Frank Zhang, President of Hikvision MEA, remarked, “Hikvision supports sustainable urban planning by empowering traffic departments to address congestion and transportation challenges.” He further emphasized, “Our system’s openness fosters a secure and reliable platform for developing smart and green cities. Additionally, our solar technology is extensively utilized in remote areas, while our smart street lighting solutions reduce energy consumption by 20-30%, promoting intelligent urban transportation and advancing global sustainability objectives.”
Hikvision’s presence at the ITS World Congress in Dubai underscored its leadership in integrating AIoT technologies to drive safer, smarter, and greener mobility solutions. The engaging presentations and advanced product demonstrations captured significant attention from industry partners and customers, reaffirming the company’s role as a pioneer in shaping the future of urban transportation. As the world moves towards more intelligent and sustainable transportation systems, Hikvision remains at the forefront, embracing AIoT to create a safer, smarter, and greener future for all.
To find out more about Hikvision’s advanced traffic and public transport solutions, please explore the Hikvision official website.
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Artificial Intelligence
Anti-Drone Market worth $7.05 billion by 2029 – Exclusive Report by MarketsandMarkets™
DELRAY BEACH, Fla., Sept. 27, 2024 /PRNewswire/ — The global anti-drone market was valued at USD 2.16 billion in 2024 and is projected to reach USD 7.05 billion by 2029; it is expected to register a CAGR of 26.7% during the forecast period according to a new report by MarketsandMarkets™. Increasing government spending on counter-drone technologies, rising incidence of critical infrastructure security breaches by unauthorized drones, and surge in adoption of aerial remote sensing technologies to safeguard critical infrastructure are attributed to the demand for anti-drone.
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Browse in-depth TOC on “Anti-Drone Market” 178 – Tables61 – Figures253 – Pages
Anti-Drone Market Report Scope:
Report Coverage
Details
Market Revenue in 2024
$ 2.16 billion
Estimated Value by 2029
$ 7.05 billion
Growth Rate
Poised to grow at a CAGR of 26.7%
Market Size Available for
2020–2029
Forecast Period
2024–2029
Forecast Units
Value (USD Million/Billion)
Report Coverage
Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Segments Covered
By System Type, Application, Platform type, Vertical, and Region
Geographies Covered
North America, Europe, Asia Pacific, and Rest of World
Key Market Challenge
Vulnerability to hacking
Key Market Opportunities
Emphasis on improving unmanned aircraft systems technology
Key Market Drivers
Growing number of illicit activities
By System Type: Hybrid systems to account for the larger market share in the forecasted year.
The hybrid segment accounted for the largest share of the anti-drone market in 2029. The trends of integrating multiple anti-drone technologies are rising since they are most effective in detecting, tracking, and neutralizing drone threats. These systems merge electronic, kinetic, and lasers, providing a comprehensive defense solution against UAVs. Hybrid systems use electronic, kinetic, and laser-based countermeasures to offer optimum protection against drones. These systems are designed to detect, track, identify, categorize, and mitigate drones at operational wide ranges ranging from a few km up to tens of km.
By Platform: The ground-based segment accounted for the largest market share in the forecast year.
The ground-based segment will hold a major share of the anti-drone market in 2029. Many ground-based anti-drone systems use several electronic technologies, such as radar, IR sensors, acoustic systems, and RF & GNSS jammers. MESA radar solutions are used mostly for counter-UAS purposes, protecting critical infrastructure, military camps, and other security-sensitive sites from unauthorized drones. One such solution is EchoGuard, a ground-based airspace management solution that contains a software-defined 3D radar that can be specific to the site. This system can identify single or multiple off-chance drones, including swarms in unauthorized areas. They provide accurate and sustained airspace surveillance for the field of view (FOV) they are configured, and both human and AI-monitored visual checks. The system can be easily transported and integrated directly with the command-and-control centers or another identification sensor for portable use, and multiple units of the system can be combined to cover vast areas or lengths of borders. Major providers of ground-based counter-drone systems include companies like EchoDyne Corporation, DeTect, Meteksan Defense, and WhiteFox Defense. Acoustics-based Discovair G2 utilizes patented microphone arrays. With 128 interconnected microphone elements, the Discovair sensor units can establish azimuth and elevation to the target in real-time using advanced digital signal processing.
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By Region: Americas are expected to hold the largest share of the anti-drone market during the forecast period.
Americas is expected to capture the largest share in the anti-drone industry during the forecast period. The growth can be attributed to protecting crucial infrastructure in the region. Governments, particularly in the US, invest in anti-drone systems for military bases, borders, and critical infrastructure. For Instance, in April 2023, RTX secured a USD 237 million contract from the US Army to provide Ku-band Radio Frequency Sensors (KuRFS) and Coyote effectors. These systems are designed to detect and neutralize unmanned aircraft systems (UAS). The contract includes stationary and mobile systems and a specified quantity of effectors, all aimed at enhancing the Army’s operations within the US Central Command region.
Key Players-
The key companies offering anti-drone companies include RTX (US), Lockheed Martin Corporation (US), Leonardo S.p.A. (Italy), Thales (France), and IAI (Israel).
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Artificial Intelligence
CluePoints Launches Medical & Safety Review (MSR) Software to Revolutionize Clinical Data Review
CluePoints furthers its commitment to delivering innovative solutions that enhance clinical trial efficiency with this latest addition to its enterprise software platform.
KING OF PRUSSIA, Pa., Sept. 27, 2024 /PRNewswire/ — CluePoints continues to transform clinical trial review and leverage its industry-leading software to enhance the interrogation, analysis and presentation of data with the launch of its latest application, Medical & Safety Review (MSR).
The tool simplifies and streamlines the medical analysis of study data through user-friendly dashboards, data manipulation and cleaning, query management and full transparency over the data history. This not only improves efficiency and communication in medical oversight, but also elevates patient safety, differentiating MSR as a smarter and unique solution.
Designed by, and for Medical and Safety Reviewers, MSR converts the manual analysis of patient outcomes, which can be prone to inefficiency and error, into an accurate, efficient process. MSR tackles time-consuming study preparation for specific visualizations by featuring a comprehensive standard visualization library as well as the ability to copy and reuse dashboards across different studies, enabling the identification of outlying values, change tracking, and improved communication for smarter clinical trials.
Other benefits of MSR include:
Enhanced medical review efficiency and reduced human errors via automated checksReduced time spent by clinical and data management teams in reviewing dataImproved collaboration with integrated review workflows across departmentsEnsured record quality and accountability with comprehensive change trackingDriving faster decision making with the proactive detection of trends and safety issuesEnsuring regulatory compliance with rule-based detection and user assignmentsAndy Cooper, Chief Executive Officer at CluePoints, commented, “We are thrilled to announce the launch of Medical & Safety Review to our growing product offerings. MSR is the latest application addition to the CluePoints platform, which includes products such as Risk-Based Quality Management (RBQM) and our Site Profile & Oversight Tool (SPOT). Together, they provide a comprehensive approach to clinical trial optimization, enhancing data integrity, ensuring regulatory compliance, and accelerating drug development. The creation of MSR ensures a more streamlined review process while prioritizing patient safety at every step and empowers medical teams to swiftly identify outliers, track data changes, and improve communication.”
To learn more about CluePoints’ award-winning solutions, please visit www.cluepoints.com
About CluePoints
CluePoints is the premier Risk-Based Quality Management (RBQM) and Data Quality Oversight Software provider. We are leveraging the potential of Artificial Intelligence using Advanced Statistics and Machine Learning to determine the quality, accuracy, and integrity of clinical trial data both during and after study conduct. Aligned with guidance from the FDA, EMA, and ICH E6 (R2), CluePoints is deployed to support central and on-site monitoring, medical review, quality risk management and to drive a holistic Risk-Based strategy in all trials. Coupled with thought leadership and consulting expertise to aid pre-study risk assessment, identification of risk controls and solution implementation, you now have everything you need to adhere with global regulatory guidance. The result is positive clinical development outcomes, increased operational efficiency, lower costs and reduced regulatory submission risk as part of the industry paradigm shift to RBQM.
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