If you’ve ever been to business school, or taken an operations management course at any point, there is always a section on Product Mix. It typically goes something like this:

CP Furniture (CEO Tim Wright) makes swanky conference event furniture. The production process for each is similar in that both require a certain number of labor hours in the carpentry department, and a certain number of labor hours in the painting department. Each table takes 4 hours of carpentry work and 2 hours of painting work. Each chair requires 3 hours in carpentry time and 1 hour in painting. During the current production period, 240 hours of carpentry time and 100 hours of painting time are available. The marketing personnel are confident that they can sell all the tables that are made. However, due to an existing inventory of chairs, they want to make no more than 60 new chairs. Each table sold results in a profit contribution of $7, and each chair sold yields a profit contribution of $5. What’s the optimum mix of chairs and tables to maximize worker efficiency, utility, and net profits?

Then the students typically turn to linear programming or something like Excel’s (semi-flawed) Solver algorithm to work through a very controlled calculation. These calculations don’t take into account the potential for stock-outs of materials at the suppliers, worker strikes, changes in customer preferences for chairs vs. tables, et cetera. So in a very real sense, our next generation of business minds are being lulled into thinking that a simple Solver output is all that’s needed in the real world. This is simply not true.

Small Molecules vs. Biologics
A small molecule is typically defined as a drug product that is of 900 Daltons in size or smaller. They generally exert their effects amidst biochemical reactions within the body. In pharmacology, small molecule as a term is usually reserved for specific molecular cases that bind to certain macromolecules to act as ‘effectors.’ In our industry, we use it a bit more loosely, but the general principles remain. With a size under 900 Daltons (< ~1 nanometer), small molecules can diffuse relatively easily across cell membranes and be transcellularly transported across intestinal epithelial cells quickly. When small molecules under ~500 Daltons are used, lower rates of clinical attrition tend to follow, which has become a consideration of note for many years (cf. Lipinski’s Rule of Five).

A biologic tends to be large and complex. They are generally made in genetically engineered cells that impose their own variation—such as with post-translation modifications—on the outcomes of the drug manufacturing processes. The FDA suggests that “Biologics can be composed of sugars, proteins, or nucleic acids or complex combinations of these substances, or may be living entities such as cells and tissues. Biologics are isolated from a variety of natural sources—human, animal, or microorganism—and may be produced by biotechnology methods and other cutting-edge technologies.”¹ Biologics can interact with challenging biochemical targets in vivo, which have thus far eluded small molecule drugs. The best examples of this are protein-protein interactions which are characterized by large, and sometimes, flat surfaces with few electrically-charged pockets.

Manufacturing of biologicals tends to be much more challenging—complexity, time, potential for difficult-to-predict failure—than for traditional small molecule drugs. Even minor or seemingly-insignificant changes in manufacturing process can cause dramatic changes in efficacy or immunogenicity (see Table 1: Characteristics of small molecule drugs compared to biologics²).

Because of the differences of these two entities, manufacturers are always faced with the real-world version of the fake-world business class challenge posed above: Should you add biologics into your product mix? If you only make biologics, should you also have a portfolio that includes small molecules? What ratio is the ‘right’ ratio for these two forms of therapy to maximize your facility’s up-time and profitability? All good questions. Here are some answers:

When in doubt, diversify
This is a typically-recited statement among financial investors, because to a large degree, spreading out your risk into a variety of potential funds tends to lead to more stable and predictable profitability as time goes on. In this way, diversification can contribute to stability by averaging the components of noise from a variety of different assets. The same could be true, though not necessarily so, in diversifying your product portfolio, up to and including combining production of small molecules and biologics.

Cost to the consumer matters. A lot.

Just because there’s a breakthrough drug doesn’t mean that people will buy it. Or that insurers will pay for it. The issue here is fundamentally market penetration. You can’t get a return on investment for a complex manufacturing process if you overprice the drug. You can readily find a variety of cost models for small molecules vs. biologics, but a relatively accurate one puts the cost of an averaged, daily small molecule treatment at ~$1/day. Whereas biologics can easily be $22/day or greater.³

Research conducted by Evaluate Pharma several years ago positioned biologics as a growing trend, where biologic products accounted for 17% of sales of the top 100 pharma products in 2004; 34% in 2011 and were forecasted to represent 50% in 2016. We now know the composition of the current Top 10 pharma products and the domination in large part thereof from biologics. So there is real demand and dollars there. But small molecules are assuredly still very effective ligands, can be quicker to development, and had also been approved by FDA at a rate of 2:1 over biologics. Although, that’s also subject to a considerable amount of year-to-year fluctuation, averaged industry pipelines being what they are. Also, don’t forget that having the option now of combining biologics with more well-defined chemical entities in the form of antibody-drug conjugates (immunoconjugates) represents yet another way to diversify product mix. 

Optimizing product mix
Understand that a product mix in this context has two fundamental components: Product mix width and consistency.* Product mix ‘width’ refers to the number of product lines ‘wide’ within a facility. This is diversification of the portfolio. Product mix ‘consistency’ refers to how closely related the product lines are in terms of end use, production requirements, distribution channels or any other business concern. 

In order to properly appraise the optimal product mix for your facility, run length, batch sizes, distribution, costing analysis (per batch), error (defect, failure) rates, total uptime/downtime, and capital intensity must be used to solve this. It becomes a bit more complicated than the table and chairs example, but the overall principle is the same and becomes a formulation of linear optimization. Some of this shares a pedigree with John von Neumann’s conjecture on the theory of duality from game theory.

Additionally, my Author’s Pro tip: Approaching your product mix calculations properly matters. A lot. Dantzig’s original example for linear programming was to optimally assign 70 people to 70 different roles (jobs). The number of configurations for this exceeds the number of particles in the known universe. For a reasonable supply chain complexity that could exceed this, you may not get an answer for a long, long time. Try a linear optimization method using your calculated inputs and save yourself from an incorrect answer, as well as perhaps 110,000 years of computation time. 

*There’re really 4 components, but the additional two are the product mix ‘length’ and one is product mix ‘depth.’ The product mix ‘length’ is how many different sellable items there are within a product line. This is generally one in pharma. The product mix ‘depth’ is one that we can virtually disregard in the pharmaceutical industry, because it refers to the number of different variations within a vertical of the product mix. One setup (train) of a small molecule or biologic produces a (hopefully QbD) output. There aren’t different flavors.

References
1. United States Food and Drug Administration. (2019). What are “biologics” questions and answers. https://www.fda.gov/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CBER/ucm133077.htm
2. Declerck PJ. Biologicals and biosimilars: a review of the science and its implications. Generics and Biosimilars Initiative Journal (GaBI J). 2012;1(1):13-6.
3. GaBI Online – Generics and Biosimilars Initiative. Opportunities for biosimilar development. Mol, Belgium: Pro Pharma Communications International; [cited 2012 Jun 29]. Author’s note: remember that prices are continuously in flux, and so even more recent calculations on this aren’t necessarily more accurate.

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Ben Locwin

Ben Locwin, PhD, MBA, MS, MBB began his foray into healthcare decades ago after he started out as an astrophysicist. He is a popularizer and communicator of science, and has worked in a variety of pharmaceutical organizations (small molecule and biologics), medical device organizations, and within hospitals, clinics, and emergent care centers bringing better healthcare to the end user (i.e., the patients!).