Pathway Engineering

Many biotech solutions require diligently engineered biochemical pathways. Such pathways may be biosynthetic, incorporating feedstock input in a bioreactor and creating a product output. Other pathways may deliver drugs through the human body and eventually metabolize reactants. Other, related pathways may be immunizing and/or signaling.

In silico technology can greatly support and accelerate pathway engineering by simulating and validating pathway candidates, spotting bottlenecks and toxic intermediates, identifying and testing alternative (or no) catalysts. This reduces experimental burden, saving time, material and analytical resources. Therefore, our proprietary platform is providing the necessary simulation, refinement and molecular and ambient validation, visualization and documentation functions and features.

Note, that our approach to pathway simulation is partly based on a robust, noise-tolerant stochastic process model, replacing approximative, deterministic differential equations (ODEs).

What pathways do we engineer?


Past and ongoing projects with different partners include:

  • Engineering pharmacokinetic pathway for nanobody-drug-conjugate (NDC) life cycle supporting anti-cancer diagnostic and therapeutic objectives.
  • Simulating, visualizing, stabilizing and optimizing an established pathway for anaerobic digestion of agricultural biomass feedstock and production of methane in an industrial fermenter.
  • Initiating development of a microbial polyester degradation pathway for household biomass, involving augmented esterase, lipase and cutinase enzymes.
What are pathway engineering functions and features of our platform?


Our proprietary platform allows in silico pathway engineering for specific medical and industrial application. Key functions and features include:

  1. Molecule Transition Matrix
    1. Define molecular space:
      • Input molecules (e.g. feedstock);
      • Output molecules (e.g. products);
      • Intermediates;
      • Catalysts (microbial or abiotic).
    2. Set ambient parameters:
      • Temperature;
      • Pressure;
      • pH;
      • Light;
      • Etc.
    3. Set reactor parameters:
      • Reactor volume;
      • Time in reactor;
      • Etc.
    4. Estimate transition rates:
      • Quantities from stoichiometry;
      • Rates from dynamic ODEs, Michaelis-Menten, etc.
      • Activation effects;
      • Inhibition effects;
      • Saturation effects.
        .
  2. Pathway Simulation
    1. Equilibrate transition rates…
      • …by stepwise hyperplane relaxation;
      • …by max likelihood for missing entries.
    2. Simulate by trajectory…
      • … possibilities (candidate model);
      • … probabilities (probabilistic model);
      • … rates (kinetic model).
        .
  3. Simulation Refinement
    1. Add, omit and/or augment molecules in  matrix (NEA);
    2. Adjust rates (MHM).
      .
  4. Insights Validation
    1. Analyze sensitivities to input parameters & assumptions;
    2. Characterize (possibly toxic) intermediaries;
    3. Analyze timing and delays;
    4. Assess implications for…
      • …molecule design;
      • …ambient design;
      • …reactor design.
How do we differentiate?


As a focused in silico solution and service provider, we are offering dedicated collaborations, exclusive partnerships and joint ventures. We differentiate from other providers with such offerings in terms of application breadth, quantitative scrutiny and solution scope. These three features may be critical success factors for your biosolution development and/or productization project…

  1. Breadth of Application
    We are serving multiple industrial segments, including life science, chemicals, energy, utilities, food, textiles and construction material. The versatility and scalability of our in silico technology is anchored in the joint biological and chemical principles of the diverse industry applications.

    Resulting benefits:
    • Our in silico platform allows cross-industry benchmarking and validation, re-purposing of bioproducts, and extended data utilization and machine learning.
    • Our in silico platform allows efficient configuration to new and completed applications, without the burden of complexity-driving and time-consuming customization.
    • Our in silico platform promotes out-of-the-box thinking and guides cross-discipline innovation on a shared scientific basis.
      .
  2. Quantitative Scrutiny
    Data acquisition in vivo or in vitro, through lab experiments, typically comes at a high price. In silico technologies can compute insightful parameters and indicators with lower time and resource spending. Yet, type and accuracy of these parameters strongly depends on the underlying in silico technology. Some AI approaches generate only heuristic data. Stochastic approaches yield probabilities. Not all scores meet decision makers’ expectations.

    Our approach:
    • We are offering advanced metrics supporting design decisions at various levels. These metrics are scientifically grounded, explainable, understandable, justifiable and comparable.
    • For these metrics, we are offering proprietary and/or syndicated benchmarks, internal experience and external reference values.
    • We are monitoring consistency between metrics and benchmarks, securing plausibility of the overall design parameters, and engineering trust in the solution, conclusion and insights.
      .
  3. Scope of Solution
    Computational development of biosolutions does not end with proven molecule manufacturability, affinity and function. In silico technology takes biosolution development on a journey much further and broader,  leading from early target projection via molecule design and pathway engineering to a computational validation, trial and/or approval simulation and finally to IP protection.

    We differentiate by supporting a fairly large portion of this in silico capability spectrum:
    • Project Targets: Mine biological data sets, screen patent databases and identify targets. Prioritize targets based on scientific insight, technological possibilities and commercial opportunity.
    • Design Molecules: Generate hit and lead molecules for a given purpose. Determine their natural structure(s), ascertain their function(s) (QSAR) and preview properties (ADME) in their target environment.
    • Engineer Pathways: Determine how molecules behave in their biological network. Consider molecule features (e.g. solubility, permeability, stability, toxicity) and interaction (e.g. activation, inhibition, catalysis) along their metabolic or regulatory, human or industrial pathway. Adjust the pathway by modifying molecule(s), ambient conditions etc.
    • Simulate Trials (currently not implemented on our platform): Model cells, tissue, organs, patients and cohort permutations in a virtual clinical trial environment. Predict outcomes and adjust original model parameters to secure clinical and approval success.
    • Protect IP: Secure the ultimate commercial success of your innovation by utilizing in silico technology for patent formulation. This may even be extended to peparing regulatory registration, certification or approval, hazard classification, etc. 

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