This interview is with Vardan Ter-Antonyan MS, LSSMBB, Founder and Managing Principal, Ter-Antonyan Consulting LLC.
For Connectively.us readers, how do you introduce yourself today—as a Founder and Managing Principal in pharmaceuticals—and what specific kinds of R&D problems are you most often called in to solve?
Im the Founder and Managing Principal of Ter-Antonyan Consulting LLC, a consulting firm focused on saving companies time and money by eliminating technical and operational bottlenecks, allowing companies to focus on scaling up with confidence and launching products quickly and efficiently.
The industries we serve are:
- Pharmaceutical
- Medical Device
- Dietary Supplements
- Consumer Products
- Food
- Beverage
Specific R&D problems:
- Increasing solubility and bioavailability of lipid active ingredients.
- Modifying the release of active ingredients from immediate to sustained.
- Creating novel drug delivery systems.
- Formulating complex nano-emulsions, liposomal drug delivery systems, cyclodextrin inclusion complexes, and self-nanoemulsifying drug delivery systems using nanoscience and nanotechnology.
- Formulating scalable and novel solids, liquids, and semi-solids that perform well on the market.
What were the pivotal choices or moments that took you from bench science to leading R&D organizations and building a consulting practice focused on formulation, scale-up, and commercialization?
I have 20+ years of experience in R&D, formulation, and commercialization of products, as reflected on my LinkedIn. Because of that, the number of requests for my help became so overwhelming that I opened my own firm to provide assistance.
The services mirror market needs and the requests coming from CDMOs and brand-name companies that need help.
Our services include:
- Formulation and Research & Development of products — from solids (powders, tablets, capsules) to liquids (injectables, nano-emulsions, mouthwashes) and semi-solids (creams, gels, lotions).
- Scale-Up and Commercialization: process development and product development from concept to launch.
- Regulatory and Quality: FDA regulatory submissions (21 CFR 210/211, 21 CFR 111/117, DMF, 510(k)), as well as CAPAs, deviations, OOS, RCA.
- Operational: Lean Six Sigma projects.
- Executive: company lifecycle phase management, and more.
When deciding whether to build a capability in-house or bring in outside experts, what is your decision framework, and can you share one project where that call measurably improved speed or reduced risk?
Our decision-making when it comes to hiring permanent employees versus consultants is simple: We hire full-time, permanent employees who can do work that will still be needed five years down the road. We hire consultants temporarily if help is needed for a specific, niche project for which we will not need ongoing support in the future. If the market is moving toward a particular area of expertise or science, we hire, but when an obscure client wants something specific, we find a consultant who can satisfy the request.
For example, we had a client who had a gummy with an oil-in-water nano-emulsion in it, but the issue was that the active ingredient was delivered into the blood too quickly and they needed to slow down the release from 2 hours to 8 hours. This was a one-time deal, and we hired a specialist who was able to satisfy the client within an hour. After the client was satisfied, we never heard from them again.
Once you’ve committed to building internally, how do you structure the first 60–90 days of work to burn down the biggest uncertainties while keeping timeline and budget credible with stakeholders?
I structure the first 60–90 days around evidence.
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Days 0–30: Define the business problem, success criteria, technical risks, required skills, and the few assumptions that could derail the project. Establish a baseline for cost, timeline, and current performance.
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Days 30–60: Run small, focused experiments against the highest-risk assumptions. In formulation development, that might mean confirming API solubility, physical stability, manufacturability, and analytical capability before investing in equipment or attempting scale-up.
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Days 60–90: Have enough evidence to decide what to continue, change, stop, or outsource. Present stakeholders with actual data, remaining risks, spending to date, and the next decision point.
I keep the timeline and budget credible by planning in stages. Each stage has:
- a defined question
- a spending limit
- a deliverable
- a go/no-go decision
Early estimates are presented as ranges and updated as evidence replaces assumptions. That gives leadership visibility without pretending we know more than we do.
For a poorly soluble BCS Class II molecule, what is your go-to decision pathway—from early screens to selecting between lipid systems, SNEDDS, nanoemulsions, polymers, or lyophilization—to balance bioavailability, manufacturability, and cost of goods?
My first step is to determine whether poor absorption is mainly caused by the crystal lattice, low aqueous solubility, precipitation after dissolution, or some combination of the three. I look at dose, pKa, logP/logD, melting point, solid form, permeability, chemical stability, and solubility across GI pH. I also test in biorelevant media because simple buffer solubility can give a misleading picture.
Next, I run small parallel screens in oils, surfactants, cosolvents, and pharmaceutical polymers. The goal is to compare realistic drug loading, dilution behavior, precipitation risk, stability, and the amount of excipient required to deliver the clinical dose.
If the molecule is highly lipophilic and dissolves well in digestible oils, I usually examine a lipid-based system first. I move toward SNEDDS when the formulation can carry the full dose, disperse rapidly in gastrointestinal fluid, and keep the drug solubilized during dispersion and digestion. Dynamic dispersion and lipolysis testing are important because a clear concentrate can still precipitate after administration.
A conventional nanoemulsion may make sense when the final product needs to be an aqueous liquid, but it usually brings more physical stability, microbial control, packaging, and shipping considerations. For oral capsules, a SNEDDS concentrate is often easier to manufacture and transport.
If I need to load hydrophilic and lipophilic active ingredients into the same drug delivery system, I go with liposomes because hydrophilic actives (for example, vitamins C or B) can be encapsulated in the core of the liposome and hydrophobic actives (for example, vitamins A, E, and D) can be encapsulated in the membrane of the liposome.
I treat lyophilization and spray-drying as a downstream enabling step for a promising formulation that cannot remain stable as a liquid, such as certain nanosuspensions or drug complexes. Their cycle time, energy use, equipment requirements, and scale-up cost generally make them a later choice for a cost-sensitive oral product.
The final selection is based on the lowest-complexity system that delivers the target exposure at the intended dose. Before committing, I compare bioavailability potential, drug loading, stability, process scalability, capsule or dosage-form size, excipient acceptability, packaging, and cost per dose. That prevents an impressive laboratory formulation from becoming an expensive manufacturing problem.
What design-for-scale principles do you rely on to take a lab formulation to reliable multi-site manufacturing and broad healthcare use, including in low-resource settings with heat, humidity, or limited cold-chain?
I design for the hardest expected manufacturing and distribution conditions from the beginning. If a product may be used in a hot, humid region with limited cold-chain capacity, those conditions belong in the development plan before the formulation is finalized.
My first principle is process simplicity. I favor widely available excipients, standard equipment, short processing times, and operating ranges that can tolerate normal variation. A formulation that only works with one mixer, one supplier, or a very narrow temperature range will be difficult to transfer across sites.
I identify the critical material attributes and process parameters early.
- Particle size
- Moisture
- Mixing order
- Shear
- Temperature
- pH
- Hold time
These factors may all affect product performance. Instead of relying on one successful laboratory batch, I deliberately test the edges of the proposed operating ranges. This shows whether the process is genuinely reliable before it reaches commercial scale.
For multi-site manufacturing, the control strategy must define what matters and how each site will measure it.
- Raw-material specifications
- Sampling methods
- In-process controls
- Analytical methods
- Equipment equivalency
- Acceptance criteria
These elements should be transferable without depending on knowledge held by one scientist. I also use pilot and engineering batches to confirm that scale-dependent effects, such as heat transfer, mixing, filtration, and drying, remain controlled.
For low-resource settings, I prioritize:
- Room-temperature stability
- Low moisture sensitivity
- Compact packaging
- Simple administration
- Minimal preparation by healthcare workers or patients
Where possible, I choose dry formats or concentrates over water-heavy products. I use accelerated and long-term stability studies that reflect the intended climatic zones, including:
- Heat
- Humidity
- Temperature cycling
- Shipping stress
Packaging is part of the formulation strategy, especially when protection from moisture, oxygen, or light determines shelf life.
Finally, I evaluate cost per usable dose rather than raw-material cost alone.
- Yield losses
- Testing
- Packaging
- Storage
- Shipping
- Cold-chain failures
- Field waste
These factors can outweigh the price of an excipient. The best design is one that different manufacturing sites can reproduce, the supply chain can support, and the patient can use correctly under real conditions.
Which early regulatory and quality moves (e.g., phase-appropriate GMP, assay readiness, prior interactions with FDA) have most consistently de-risked scale-up and accelerated the path from first-in-human to commercialization for you?
The most valuable early move is to define the target product profile and critical quality attributes before the formulation and process become difficult to change.
Key attributes to consider:
- Dose accuracy
- Potency
- Impurities
- Dissolution or release
- Microbial quality
- Stability
- Container-closure requirements
I use phase-appropriate GMP, but I do not interpret that as relaxed documentation. Early clinical manufacturing may not require every commercial control to be fully validated, but materials, batch records, deviations, equipment, training, data integrity, and product disposition still need a controlled system. The quality system should be able to mature without rebuilding everything between phases.
Elements that should be controlled early include:
- Materials
- Batch records and deviations
- Equipment and training
- Data integrity
- Product disposition
Analytical readiness is another major de-risking step. Before first-in-human manufacturing, I want a qualified assay that can measure potency and impurities, indicate stability, and support release decisions. Full validation can follow at the appropriate stage, but a weak assay can make formulation, stability, and scale-up data difficult to interpret.
Assay readiness considerations:
- Reference standards
- Sample preparation
- Method suitability
- Impurity tracking
I also start stability studies early using representative formulations, processes, and packaging. Short-term accelerated data can expose degradation, moisture sensitivity, precipitation, or packaging problems while there is still time to make changes. Retaining samples from important development batches also helps investigate later questions.
Stability testing can reveal:
- Degradation
- Moisture sensitivity
- Precipitation
- Packaging problems
For FDA interactions, the best value comes from asking focused questions while the program still has flexibility. A pre-IND meeting can help confirm the development plan, clinical starting strategy, CMC expectations, and the acceptability of proposed studies. The briefing package should present the available data, the company’s proposed position, and a specific question that FDA can answer. A broad request for general advice usually produces less useful feedback.
Finally, I establish change control and comparability planning before major scale-up. Changes in site, equipment, batch size, raw-material source, analytical method, or container closure should be documented with a clear assessment of their effect on product quality and clinical relevance. That record becomes increasingly important as the program moves toward pivotal studies and commercialization.
These steps require some investment early, but they prevent expensive repetition of batches.
What are the 3–5 KPIs or signals you review every week to keep cross-functional R&D, tech transfer, and validation on track, and how do you act when one starts to drift?
I review five signals every week:
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Critical-path milestone status. I track whether the next major deliverables are still achievable, including formulation selection, engineering batches, method readiness, protocol approval, and validation execution. I pay more attention to dependencies than to the percentage reported complete.
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Open technical risks and assumptions. Each major risk should have an owner, a planned experiment or action, and a decision date. If the same risk remains open week after week, the team may be generating data without resolving the actual question.
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Batch and process performance. I review yield, assay, variability, deviations, rework, and performance against critical process parameters. During tech transfer, I also compare the receiving site’s results with the development-site baseline.
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Analytical and quality readiness. This includes method qualification or validation status, sample-testing turnaround, specifications, stability results, deviations, and document approvals. A delayed or unreliable method can hold up several workstreams at once.
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Aging decisions and action items. I look for decisions, investigations, and approvals that have remained open beyond their agreed dates. These often reveal resource conflicts or unclear ownership before the schedule visibly slips.
When a signal starts to drift, I first determine whether it is normal variation, a resource problem, or a technical issue that changes the project assumptions. Then I assign one accountable owner, define the immediate containment action, and set a short recovery date.
If the issue affects the critical path, budget, product quality, or regulatory commitments, I raise it early with options. Those options may include:
- changing the sequence of work,
- adding resources,
- narrowing the scope,
- outsourcing a specialized task, or
- revising the milestone.
I would rather reset an expectation with evidence than allow a small delay to become a surprise several weeks later.
Drawing from your experience in rock climbing and other extreme sports, what is one leadership habit you brought into R&D that has measurably improved how your teams assess risk and communicate under pressure?
One habit I brought from rock climbing into R&D is calling a pause as soon as something no longer matches the plan.
During a climb, small changes in weather, equipment, communication, or physical condition can become serious if people continue out of momentum or pride. You learn to stop, state what you are seeing, reassess the risk, and decide whether to continue, change the approach, or turn back. Everyone involved has the authority to raise a concern.
I use the same rule in R&D. Before an important experiment, scale-up batch, or technology transfer, the team discusses the main failure points, what warning signs to watch for, and which conditions require us to stop and reassess. If an operator, scientist, or quality colleague sees something unexpected, I want it communicated immediately, even when the data are incomplete.
This has improved how quickly teams surface problems. We can measure the effect through earlier deviation detection, shorter investigation cycles, fewer repeated errors, and fewer surprises near a major deadline. It also improves the quality of communication under pressure because people do not have to soften or hide a concern until they have a perfect explanation.
In both climbing and R&D, good risk management is rarely about eliminating every risk. It is about noticing when conditions have changed and speaking up early enough to preserve your options.
Thanks for sharing your knowledge and expertise. Is there anything else you'd like to add?
No. Thank you for the opportunity to share information about my business and to answer important questions.