NeoTrident, along with its parent company, Suzhou NeoTrident Software Co., Ltd., passed the ISO/IEC 27001:2013 certification from the British Standards Institution (BSI). This milestone marks NeoTrident’s internationally recognized capability in information security management, strengthening its position as a secure and reliable IT provider in life and material sciences.
This certification reinforces NeoTrident’s commitment to safeguarding customer data and system security, further enhancing its product offerings like the iLabPower Collaborative Innovation Cloud. The certification affirms that NeoTrident adheres to rigorous international standards in areas such as data encryption, asset management, and system security. The company continues to prioritize security management, fostering customer trust and ensuring robust data protection across its digital platforms.
With over 1,000 R&D institutions using NeoTrident’s solutions, the ISO27001 certification adds credibility to their extensive service portfolio in fields ranging from research to production.
With the rise of electronic lab notebooks, molecular biologists and chemists are now able to collaborate more efficiently, streamlining the development of new drugs through standardized workflows. However, as the life sciences industry continues to evolve, there are several challenges that researchers face when working with increasingly complex data and processes in bio-new drug development. One of the main challenges is the need for specialized software solutions that can handle the growing demands of sequence analysis, data management, and experimental reproducibility.
Data Complexity As drug development processes become more sophisticated, the amount of data generated from biological experiments has increased significantly. Managing and analyzing this data efficiently is crucial for timely and accurate results. Complex workflows, such as gene editing, protein synthesis, and antibody development, require software tools that can handle large datasets, perform detailed analyses, and ensure data traceability across multiple experiments and teams.
R&D Costs and Efficiency Developing new drugs requires substantial investment in research and development. For laboratories and pharmaceutical companies, optimizing the efficiency of R&D processes is critical to reducing costs and shortening development timelines. Time-consuming tasks, such as manually curating sequences, calculating biochemical properties, and designing primers, can slow down research and lead to errors. Streamlining these processes with integrated tools is essential to improve productivity and ensure high-quality outcomes.
Some researchers have tried using a variety of standalone tools to manage data, but this approach often leads to fragmented workflows, data silos, and inconsistent results, ultimately wasting valuable time and resources.
To address these challenges, NeoTrident offers a solution: the iLabPower SEQ Sequence Editor. This tool, part of the iLabPower R&D management platform, provides researchers with an integrated and efficient platform for biological sequence design and analysis. Equipped with visual sequence editing functionality, the tool also allows researchers to document the design process seamlessly in the electronic lab notebook, ensuring full traceability and reproducibility.
iLabPower SEQ Sequence Editor Overview The iLabPower SEQ Sequence Editor enables users to manage the entire sequence design process—from sequence creation and editing to validation—all within a single platform. For example, in plasmid construction, a common molecular biology experiment, essential steps such as gene and vector selection, PCR primer design, pre-assembly cutting with appropriate endonucleases, and verification via sequencing results can all be conducted within the Sequence Editor. By consolidating these workflows, the platform ensures traceability and reproducibility, which are essential for reliable research. Moreover, applications like CRISPR and circular RNA construction follow similar workflows, making iLabPower SEQ Sequence Editor versatile for a range of bio-design processes.
Key Features of iLabPower SEQ Sequence Editor
Sequence Creation: The editor supports various ways to create sequences:
Import FASTA, GenBank, and other annotated sequence files.
Customize sequence labeling for efficient management and searching.
Automatically process sequences, including case conversion, coordinate generation, and sequence editing operations, saving time and reducing manual errors.
Visual Sequence Display: The editor allows users to visualize sequences as linear or circular maps, displaying annotations, primers, and restriction sites in a personalized format. This makes it particularly useful for designing structures such as plasmids, CRISPR, and miRNA.
Nucleic Acid Sequence Analysis:
DNA Property Calculation and Primer Design: Automatically calculates properties like annealing temperature, GC content, and sequence length for primer design. The built-in Primer3 tool generates primer pairs based on user-specified parameters.
Enzyme Site Display: Identifies restriction enzyme sites using the NEB-Enzyme Finder and displays them for faster sequence editing.
Open Reading Frame (ORF) Recognition: The editor automatically identifies ORFs, supporting gene expression analysis, which is crucial for drug development.
Amino Acid Sequence Analysis:
Protein Biochemical Characterization: Automatically translates DNA sequences into amino acids, enabling analysis of protein properties, including hydrophobic regions, isoelectric points, and molecular weight. It also facilitates antibody design by identifying CDR (Complementarity-Determining Region) regions critical for antigen recognition.
Comparative Analysis:
BLAST: Provides one-click submission of sequence fragments to NCBI’s BLAST tool for functional prediction.
Dual Sequence Alignment: Supports alignment of DNA or amino acid sequences, helping users visualize conserved regions and sequence variations.
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iLabPower SEQ Sequence Editor in Bio-New Drug Development
New biopharmaceuticals have shown tremendous promise in treating diseases once deemed incurable, such as cancer and genetic disorders. With its intuitive, efficient, and secure design, iLabPower SEQ Sequence Editor offers a new approach to innovative research in laboratories and pharmaceutical companies. From upstream design to downstream validation, all sequence-related tasks can be conducted on a single platform with robust data security and reproducibility.
Moreover, NeoTrident is committed to continually upgrading the software, improving user interaction, and expanding its bioinformatics capabilities to better serve the bio-new drug R&D landscape. By addressing the unique needs of researchers, NeoTrident aims to support intellectual property protection and accelerate the pace of innovation in biopharmaceuticals.
In recent years, the application of Artificial Intelligence (AI) in drug discovery and development (D&D) has become increasingly prominent. AI has significantly improved the efficiency of drug research by predicting drug efficacy and toxicity, automating the design of drug molecules, and accelerating clinical trials. Faced with the impact and opportunities brought by AI, pharmaceutical companies usually take one of three approaches: developing AI capabilities internally, purchasing mature and specialized AI platforms, or outsourcing AI-driven drug discovery and development (AIDD) to third-party providers. But which strategy is the best?
Is Fully Outsourcing Your AIDD a Safe Bet?
Many companies opt to outsource their AIDD efforts, as it seems to save time and reduce costs. However, this approach presents some significant challenges.
First, data security is a major concern. Data is the lifeblood of drug discovery, and a leak could cause severe damage to a company’s business. Once data is outsourced, it becomes difficult to ensure its complete protection. Secondly, data ownership is equally crucial. Outsourcing may result in a company losing ownership of vital data, which could weaken its competitive edge. Furthermore, the quality of services provided by outsourcing companies can vary widely. If an unreliable partner is chosen, it may slow down R&D progress or lead to inaccurate research results.
Therefore, outsourcing AIDD could lead to higher long-term costs. On one hand, outsourcing expenses may increase over time as data grows; on the other hand, the financial losses due to security or service issues might exceed initial savings.
Why Emphasize Autonomous Mastery of AI Tools and Data?
While achieving autonomous control over AI tools and data may require a larger investment in the short term, it offers considerable long-term benefits.
First, professional drug researchers are more likely to achieve better results using AI tools than external partners who may lack a deep understanding of drug research. Internal teams can comprehend research objectives more thoroughly and use AI more effectively. Additionally, owning AI tools and data ensures that a company’s intellectual property and data assets are protected, securing data ownership and preventing security breaches. Furthermore, autonomous control provides greater flexibility. Companies can adapt AI tools to their specific needs and quickly adjust to changes in R&D strategies without waiting for an outsourcing partner’s response. This approach also helps build and retain AI expertise within the company. As AI becomes a core tool in drug development, companies that possess in-house expertise will have a clear advantage. Finally, controlling AI tools and data helps ensure consistency and quality, avoiding errors related to data transfers and conversions.
In the long run, owning AI tools and data can also be more cost-effective. Once a company establishes its own AI platform, it only needs to cover maintenance costs instead of recurring, often escalating, outsourcing fees.
Does Autonomous Mastery Mean Developing AI Platforms Internally?
Autonomous mastery of AI tools doesn’t necessarily require developing them from scratch. In fact, purchasing a mature, low-barrier AI platform from a specialized provider is often a more efficient and cost-effective solution.
To facilitate the integration of “AI+Pharmaceuticals” and empower drug R&D companies to easily and independently manage AI tools and data, Trunetech offers an advanced, user-friendly AI platform called MaXFlow.
MaXFlow, developed by Neotrident, is a next-generation molecular simulation and AI innovation platform aimed at all frontline experimental scientists, computational simulation experts, and AI specialists. It covers a wide range of R&D fields, including innovation discovery and process development. MaXFlow enables users to perform drug design, predict drug properties, manage research data, and much more. Its ease of use ensures that even scientists with no prior experience in molecular simulation or AI can quickly get started.
Easily build 3D models of molecules, proteins, nucleic acids, etc.
Enhance modeling efficiency through component and workflow technology
Connect with the SDH scientific data genome platform to improve data acquisition
Open environment that integrates and encapsulates various algorithms for full algorithmic freedom
SaaS cloud model that seamlessly connects with background supercomputing resources to ensure computational power availability
Extensive APP resources for practical application scenarios, allowing molecular simulation and AI technologies to be accessible with zero barriers
Sharing of physical/AI models to capture expert experience and knowledge
A platform-level solution that provides robust file management, user role, and permission management features to ensure data security, internal knowledge transfer, and the accumulation of valuable data assets.
Conclusion
Overall, taking ownership of AI tools and data is a wise and strategic choice for drug development companies in the long term. This approach not only safeguards a company’s data assets and intellectual property, enhances flexibility, and nurtures in-house talent, but also reduces costs over time. Partnering with a professional AI platform provider is an effective way to achieve this goal. High-quality AI platforms are not only mature and easy to use but also provide strong support, enabling drug development companies to better leverage AI technology.
In the “AI+Pharmaceuticals” field, both IT professionals and pharmaceutical researchers face challenges. Regardless of the chosen strategy, clear communication and collaboration between these teams are critical. Every drug development company should carefully evaluate its AI strategy, consider whether there are better options, and determine how to use AI more efficiently to unlock greater value.