Techno Economic Analysis (TEA) for Biotech

1. Introduction

2. How are TEAs used

3. Who uses TEAs

4. When should TEAs be done

5. Steps in TEA

6. How to overcome limited data in modeling scaled up processes

7. Common pitfalls

Introduction

Bioproduction can harness the cellular machinery of microbes to produce commodities at a fraction of the environmental costs relative to conventional manufacturing. It is technically possible to cultivate microbes using a wide range of feedstocks to make many commodities including food, fuel, pharmaceuticals, cosmetics and more. Over time, humans have harnessed further production techniques, but we are still just scratching the surface of what's possible. Yet, while there is a large possibility space in biomanufacturing, only some combinations are economically viable.

Enter the TEA.

Advancements in fermentation technology: From traditional sugar-based processes producing ethanol and penicillin, to novel approaches utilizing diverse substrates like methanol and methane for generating amino acids, proteins, and other valuable products for diverse industries.

To have a truly transformative impact on the world, biomanufacturing must be scalable, commercially viable and sustainable. Techno-economic analyses (TEA) are a first step in assessing biomanufacturing business plans, which can significantly improve the chance of a positive project outcome. Notably, the industry as a whole benefits when better due diligence is applied to project funding. Funding projects with economically viable paths to market, not only improves the outcomes of a specific project, but will holistically increase the adoption and investment into biomanufacturing solutions industry wide.

How are TEAs used

Technology developers, academics, and company founders use techno-economic analyses for: 

1. Making product and process choices

2. Quantifying unit economics

3. Identifying cost hotspots and the most sensitive levers

4. Setting targets for R&D and lab

5. Fundraising from investors and winning grants

6. Making go/no-go decisions

Who uses TEAs?

TEAs are used by a variety of stakeholders in innovation. Larger companies with established production lines assess new opportunities proposed by RnD department or business development units. Investors, governments and non-profits create their own TEAs or evaluate companies’ TEAs to understand if the economic projections of new ventures are reasonable. Most large institutes have dedicated TEA teams that evaluate the viability of projects and help set targets. A gap that has begun to close is that academics and founders of spinouts and start-ups are using TEAs more often nowadays, which is leading to fewer negative outcomes. Academics should be using TEAs more frequently, as they evaluate new directions for their research and evaluate how well certain research initiatives could translate to industry. This article focuses on the biomanufacturing founder’s journey but should still be helpful to anyone interested in TEAs.

Sidebar

Techno-economic assessments go by many other names, including techno-economic analysis, techno economic model, and are closely related to Front-end Engineering Design (FEED) studies and Front-end loading (i.e., FEL 1/2/3).

When should founders do TEAs

Different times in the founder’s journey call for TEAs with different levels of detail. As the project progresses the TEA will be updated to reflect new information and deeper analysis. The path below is illustrative but could vary depending on the companies.

Understanding TEA Error Across Technology Readiness Levels: This diagram illustrates TEA (Techno-Economic Assessment) error variations at different stages, from pre-seed (+50%) to commercial manufacturing (±10%), highlighting critical milestones such as pre-series A, pilot and demo, and pre-commercial phases.

1. Ideation stage / initial business plan / pre-seed (TRL 1): 

• Before taking committed steps into a certain product choice and before seeking funding, one needs back of the envelope calculations of commercial scale production. The key is to see that the minimum cost of production is comparable to the market price of substitute products.

• If the cost of production in the optimistic scenario is 4x or 3x the cost of substitute products on the market it's likely a “no go”.  If the math ain't ‘mathing’, you need to know asap. 

• Current automated tools do not seem reliable enough to fully replace a manual analysis, lack of transparency does not give enough information to properly plan and design R&D

• A reasonable margin of error for this level of analysis is ± 50%, and this TEA takes 2 to 10 days to complete.

2. Seed stage and pre-Series A (TRL 2-3):

• A more detailed TEA is required with the main processing steps, mass and energy balance, and equipment mapped out. This level of TEA should be parameterized and focus on identifying necessary R&D improvements on the lab scale (i.e., set targets). The focus here is to find key cost drivers and levers for process optimisation, and to narrow the margin of error. Ideally, the TEA shows that even under certain conservative assumptions, there is a path to profitability. 

• One can expect to do such TEAs 1 to 2 years after pre-seed.

• These TEAs are often outsourced for several reasons, including that investors may prefer impartial third parties to do the analysis, as well as to give founders time to focus on technology development. In addition, third parties can bring valuable insights on areas outside the founders’ expertise, like downstream processing.

• The margin of error can be circa ± 25% and this TEA requires 2 to 8 weeks to complete

3. Pilot/demo: preparing for commercial scale (TRL 4-5):

• TEA at this level has more indepth knowledge of the process being modeled. The focus here is to achieve higher granularity in the process both in technical and financial aspects. At the end of this stage companies should know exactly what equipment they want to use in their scaled-up process and work on optimising their performance to hit or revise targets.

• Real-world information about the integrated operations of machines will inform the TEA. Certain data points from the pilot/demo will now be inputted into the commercial scale model. Data about water usage, electricity usage, uptime of the facility, labor, purity can all be updated during this phase. After this stage, technology developers should have all the R&D data to go to the commercial scale.

• Note that it is possible for founders to use CMOs instead of building their own pilot/demos. In the case that founders do build their own, then they will also need a detailed engineering design (FEL3) before building the pilot/demo scales. 

• The process should be optimised and the next step should be to make sure that all the steps in their facility work synchronously at their full capacity.  Timing of this level of TEA could be approximately 1-3 years after Series A

• This model can be used to greenlight the more laborious, precise, and expensive analysis in the next step.

• The margin of error can be circa ± 15% and this TEA requires 1 to 4 months to complete.

4. Commercial scale: Building First of a Kind Commercial (TRL 6-8)

• This requires an FEL-3 analysis (i.e., Front-End-Loading 3 approach) it will be location specific, and include piping and other supporting services closely estimated, and have binding quotes from vendors for long-lead time equipment)

• This work will typically be done in coordination with an Engineering Procurement Construction (EPC) company that will design the final layout of the facility. This is the most challenging phase, which most companies do not reach. It could be in the range of 2-4 years after completing the pilot/demo facilities.

• The margin of error for the economic estimates can be circa ± 10%. The models are built on top of previous ones and can take 2 to 6 months.

Steps in TEAs

Every level of TEAs can be built in eight main steps, but the level of detail in each step varies, leading to different error margins. Note that some steps may be done in parallel with others. 

Steps in a Techno-economic analysis

TEAs can be made using many tools, such as MS Excel, Google Sheet, Python or BioSTEAM, or using more advanced software like SuperPro Designer or Aspen. Spreadsheet-based models are most common, as they are visual and easily modified/ customized by non-experts. For a template model see the end of the article. First time modeling projects should likely begin with a spreadsheet. The other tools can play a role in providing more functionalities or leverage certain libraries. 

Tools that can be used in a Techno-economic analysis

Step 1: Establish fact base

• Identify the feedstock, target organism and the target product

• Collect key information about the microbiology (strain productivity, titer, fermentation duration), bioprocessing (machine type, machine efficiency), and costs of inputs.

• Research the characteristics and metabolism of the target organism

• Decide on the following about the model:

  1. Decide the target production scale

  2. Set the location of the facility 

  3. Select fermentation type and mode (single or multi scale fermentation; fed-batch or continuous)

  4. Decide on carbon feedstock choice

Step 2: Process Flow Diagram

Identify the processing steps that enable the production of the final product

• Design downstream processing

• Sketch the end-to-end production chain 

• Choose each individual equipment item in the production chain

• Identify atypical equipment

• Identify auxiliary equipment

• Decide cooling system and water recirculation architecture

• Validate with experts for any uncertain elements

Step 3: Mass Flow

Quantify the inputs and outputs of the evaluated process

• Based on the metabolism of the target organism, calculate the type and amount of feedstocks needed and the biomass or product output

• Evaluate the mass flow of each unit operation in the process, taking into account of losses and changes of biomass or product composition

• Data inputs will be a mix of lab and theoretical data. Certain lab data will be far too conservative compared to what is possible at scale (such as volumetric productivity), while certain theoretical maxima data may be impossible to achieve in practice. Hence, important assumptions must be justified and sensitivity analysis should be performed

Step 4: Energy Use

Estimate the energy consumption of each unit operation.

• Uses empirical, first principles or parameters provided by equipment vendors to calculate the energy consumption of each unit operation, in the form of electricity, cooling water, steam, natural gas, etc. as needed.

• Double check big cost drivers, like fermentor agitation and cooling systems

• Check if your fermentor has sufficient aeration and agitation

Step 5: Equipment scaling

Select the suitable equipment and their respective scale, estimate the equipment cost for the evaluated process.

• Compare between equipment that has similar function and select the optimal equipment

• Collect scale and price data for the equipment pieces

• Estimate equipment costs using scaling factors etc

• Validate major equipment pieces with vendor quotes if needed

Where C is cost, A is the scale attribute, n is the cost scaling exponent (usually around 0.7), and subscripts a and b represent the modelled and reference equipment, respectively.

Step 6: Cost of Goods Sold

Calculate the cost of goods sold based on the process input, output, and energy consumption.

• Summarize the raw material use and utility use

• Estimate the labor costs based on location, production steps and scale

• Estimate the other indirect costs based on the direct costs

• Estimate capital costs based on equipment costs

Step 7: Minimum selling price

Make a financial projection utilizing discounted cashflow, to determine the minimum product price for the project to breakeven

• Select financial parameters, including debt:equity ratio, capital expenditure schedule, loan term, interest rate, discount rate etc.

• If possible, assess market price of substitute products, and determine the target price

• Perform discounted cashflow analysis

• Calculate the Net Present Value at target price, Internal Rate of Return, Minimum Selling Price, Payback period 

Where n spans the years of facility operation until end of life, and the discount rate is equivalent to the weighted average cost of capital for the company (usually between 5% to 15%)

Step 8: Sensitivity analysis

Conduct sensitivity analysis on the parameters that were identified to have a high uncertainty or volatility, for example input unit prices (e.g., carbon feedstock).

• Select high impact parameters for sensitivity analysis

• Select sensitivity analysis type (e.g. single parameter, Monte Carlo, etc.)

• Iterate and document the sensitivity analysis result

• Identify the sensitivity of the selected parameters

• Produce plots for the results and interpret

Typical sensitivity analysis plots: Spider Plot (A) and Tornado plot (B)

Sensitivity analysis visualisation

Results

Deliver a simple guideline for parameterized model and justify parameter values

Report results in easily digestible format such as the Exec summary example below.

Example of Process Flow Diagram

TEAs can be done in-house but certain challenges arise that can benefit from leveraging an external partner to add value. Cx Bio is a TEA provider that has specialized in electrochemistry and fermentation processes with applications in gas and liquid fermentation of whole biomass, precision fermentation, food lipids, biofuels, surfactants and more. As a result, Cx Bio brings a wide range of tools to the table that accelerates TEA iteration, increases accuracy and can save founders time and money.

How to overcome limited data in modeling scaled up processes - where your TEA partner can help.

Data limitations will occur in a few categories. 

1. Microbial performance

• Energy efficiency of substrate conversion, product concentration or yield.

• Titre and volumetric productivity

• Understanding when to use lab vs theoretical data

2. Process chain unit operations (i.e., machines) 

• Especially for downstream processes which are usually not in the focus of early stages of a new biomanufacturing start-up

• Complication brought by unexpected impurity profiles of input materials

3. Equipment costs

• These can be sourced from three main places: publications and reports, calculated from engineering books, and obtained from vendors. It will be important to scale equipment appropriately. This can be time consuming and error prone. Working with vendors requires a balance between providing needed specs without entering into detailed technical discussions and avoiding false precision.

4. Raw materials costs

• It may be necessary to make a decision on the location of the theoretical facility. Many prices can be found in public sources, however one should be cautious of the characteristics of the materials (e.g., quality, purity, quantity, pressure, etc). A common pitfall in DIY TEAs is using lab scale or pharma prices for certain equipment and materials.

Common pitfalls

• Having a too optimistic uptime or product recovery

• High uncertainty in Lang factors

• Oversimplification of expensive processes

• Unrealistic scale of certain equipment

• High uncertainty in reactor costs

• Misusing standards for a biomanufacturing class

• Unrealistic volumetric productivity 

• Omitting certain equipment

• Mistakes in cooling systems

• Omitting taxes

• Not communicating error margins to stakeholders

Cx Bio can assist you with:

• Experience with process flow diagrams (PFDs)

• Downstream processing (DSP) know-how for food, fuel, lipids, and chemicals

• Databases: (for example: https://www.cxbio.io/resources)

Biological parameters, Bioprocess parameters, Equipment costs, Scaling factors, Capital and Opex factors, Raw materials costs, TEA database with extracted parameters

• Connections to researchers, vendors and processing experts for verifications

• Experience in modeling processes at different stages and scales, and using various tools

Comparison of bioreactor unit costs with sizes, highlighting data from literature and calculations. The graph shows a decreasing trend in CSTR unit cost per cubic meter as the bioreactor size increases, referencing various studies. Key components considered include vessel, heat exchangers, and pumps.

We are here to assist you on your scale-up journey in the bioeconomy. 

>>>If you would like to receive our back of the envelope TEA template, please let us know in a comment below and we will send them out in a few weeks. To keep up to date with our announcements follow us on Linkedin Cx Bio and subscribe to our newsletter.

Please don’t hesitate to reach out to share your thoughts!

Acknowledgments:

Thank you to the co-authors, Shan He, Milena Ivanisevic, Ievgen Duboriz, Dorian Leger, as well as the valuable inputs from contributor Andrew Stewart, and the review of Enrico Orsi. Cover image by NASA modified by Cx Bio

About Cx Bio 

Cx Bio is Luxembourg-based software and services provider specialized in economic and environmental impact assessments of biomanufacturing processes. The core team has a diverse set of expertise ranging from molecular biology, economics, accounting and chemical engineering. Cx Bio works with a wide range of organizations, including universities, non-profits, early stage startups and large corporations. For more information please visit www.cxbio.io, our Linkedin and our Featured Articles in the press.