Secure, Scalable Biological AI Services for B2B and Academia. Unleash AI’s Full Potential and Accelerate Discoveries with BioLM.ai

What industry needs to leverage the transformative power of AI 

The emergence of powerful artificial intelligence (AI) tools has ushered in a transformative era for biotech. Widespread development of publicly available Bio-AI models has demonstrated their potential to address some of the biggest challenges facing the industry across sectors, from antibody design and enzyme engineering to biosecurity. Yet we haven’t seen widespread adoption of these tools by the industry. 

Accessibility bottlenecks, the need for external technical expertise, the rapid evolution of AI tools, and the time, effort, and cost required to implement them keep these solutions just out of reach for the majority of industry players. That’s why we developed BioLM—a cloud-based platform that not only delivers blazing fast bioinformatics and AI solutions but that also addresses many of the operational challenges that keep AI out of R&D efforts. 

Our expertise in MLOps, MLEngineering, biology, and data science enable us to connect you with the solutions you need so that you can do what you do best: make groundbreaking discoveries.    

Stuck in the Starting Blocks: AI-Based Biotech Models Face Accessibility and Implementation Hurdles

AI-based biotech models hold immense potential for revolutionizing biotech R&D. However, significant barriers limit their widespread adoption:

Technical Bottlenecks:

  • Expertise gaps: Model creation and use often requires expertise in coding, machine learning (ML), and devops, necessitating expensive in-house teams or outsourced data management and analysis.
  • Fine-tuning complexities: Promising models often demand sophisticated fine-tuning to address specific research needs, imposing significant technical challenges.
  • Limited access: Access to the latest models is limited by technical barriers and complex licensing agreements.
  • Reliance on external expertise: External vendors are required for model inference and deployment, introducing delays and hindering internal control. 

Implementation Bottlenecks: 

  • Production ambiguities: Unstandardized processes for transitioning validated models to production cause inefficiencies and delays. 
  • Automation roadblocks: Automating research models for production scale presents a significant engineering hurdle.
  • Time and financial resources: Infrastructure setup and engineering require significant time and financial resources better spent on core scientific activities.
  • Limited adoption: Failure to internally disseminate tools restricts organization-wide adoption, limiting their implementation and ultimately, their ROI.

Opportunity Costs:

  • Resource drain: Investments in cloud infrastructure, AI vendors, and in-house ML teams drain resources and limit adoption by smaller organizations.
  • Unfair competitive advantage: Large biotechs with internal ML teams and the financial resources for leveraging the latest models have a significant competitive edge.

Data Privacy Concerns:

  • Data ownership: Many solutions take ownership over data and intellectual property (IP), forcing researchers to achieve the benefits of AI at the cost of data and IP control. 
  • Data leakage: Many solutions CROs cannot guarantee data privacy or prevent IP loss, and offer limited internal knowledge transfer.

How BioLM.ai Solves the Accessibility and Implementation Challenges of Biotech Models

BioLM.ai is a purpose-built solution designed to address each and every one of these challenges. We do this in four key ways:

1. Democratizing access:

  • User-friendly platform: Our platform removes the need for technical expertise, allowing you to focus on your science. 
  • Pre-trained models: BioLM.ai provides access to a diverse range of pre-trained bio-sequence language models, eliminating the need for extensive pre-training efforts.
  • Cost-effective solutions: Flexible pricing models enable you to access powerful computational resources at affordable rates.

2. Simplifying implementation:

  • Cloud-based infrastructure: We manage all infrastructure complexities, including GPU provisioning and scaling, so you can focus on discovery.
  • Automation tools: Our platform automates many tasks, including model deployment and data management, eliminating implementation headaches.
  • Fine-tuning capabilities: BioLM.ai allows users to fine tune pre-trained models on specific datasets, so you can tailor models to your needs.

3. Overcoming skill gaps and resource constraints:

  • Expert services: We offer expert consulting services to assist users with insufficient data science or DevOps expertise.
  • Scalable infrastructure: BioLM.ai automatically scales to meet the evolving needs of your research programs, eliminating resource constraints.

4. Addressing data privacy concerns:

  • Secure cloud environment: BioLM.ai utilizes secure cloud infrastructure to ensure the privacy and security of your data.
  • On-premises deployment options: We offer on-premises deployment options for groups requiring the highest level of data security.
  • Data ownership: You retain ownership of your data and intellectual property.

Advance your discovery and development with BioLM

BioLM.ai is a versatile tool that allows you to run powerful protein and DNA sequence classifiers, inference models, explainers, and custom de novo sequence generators in only seconds via fast, scalable, and GPU-backed REST APIs. The platform supports several use cases:

  • Antibody Engineering: Predict antibody sequence affinity and specificity.
  • Biosecurity: Screen sequences before synthesis, and reduce dual use risk of BDTs.
  • DNA Sequence Modeling: Predict functional elements and genetic variations, and enable codon optimization.
  • Enzyme Engineering: Predict enzyme and activity and stability to design and optimize enzymes for use in a variety of applications.
  • Protein Engineering: Predict structure-function relationships and generate novel proteins with desired characteristics.
  • Single-cell Genomics: Enable precise cell type classification and uncover novel cell populations.

While BioLM.ai was developed to eliminate the need for extensive technical expertise, our flexible platform also allows experienced data scientists to customize the platform for their unique research needs. Users can fine-tune massive NLP models, publish personalized API endpoints, and build custom pipelines, applications, and dashboards with our APIs and chat-agents. A wide variety of models have been implemented within BioLM.ai to meet all research needs. You can explore our APIs and model implementations here.

The Biorevolution Begins

One only need look at real-time chatbots, recommendation systems, and newsreels to grasp the transformative potential of AI-powered bio-models. We are on the precipice of a biorevolution: already, companies like Ginkgo Bioworks are demonstrating what’s possible when pairing high-throughput modeling and screening with synthesis. Their success—and the success of others—depends on combining AI-powered infrastructure with the domain expertise necessary to turn AI-enabled discoveries into new therapies and robust biosecurity screening to ensure their safe and responsible development. 

You have the domain expertise, and at BioLM we’re committed to bring you the infrastructure. We invite you to leverage our deep expertise to navigate this ever-evolving landscape, ditch the infrastructure headaches with our future-proof setup, and let us craft custom pipelines built just for you so you can stop wasting time, start innovating, and outpace the competition. 

To learn more about BioLM and how our platform can support your AI-driven research, visit our website or send us a message. We’d love to hear from you!

Author: Zeeshan Siddiqui