OfferReady Dossier

Candidate: Dr Sofia Reyes · Role: Scientist, Assay Development (Oncology), Aldbrook Therapeutics

1. Role and company research brief

Company snapshot. Aldbrook Therapeutics is a clinical-stage biotech in Cambridge developing targeted oncology biologics, specifically antibody-drug conjugates (ADCs) and bispecific antibodies. "Clinical-stage" means they have at least one candidate in human trials, so the assay work supporting those programmes must be robust, documented, and transfer-ready, not exploratory.

What this team is likely working on. An Assay Development team at an ADC or bispecific company spends its time building cell-based potency and cytotoxicity assays that measure how well a biologic kills target-expressing tumour cells. For ADCs this means target-dependent killing assays; for bispecifics, often T-cell-mediated killing (redirected cytotoxicity). They live in dose-response curves and EC50 or IC50 values, in 96-well and 384-well formats, read on flow cytometers and plate readers.

The pain point this hire solves. Clinical-stage companies need assays that are not just clever but reproducible and transferable to QC. They want someone who can develop an assay, make it robust, document it to quality standards, and hand it over. Pure academic skill is not enough: they need someone who thinks about variability, controls, and handover.

Three talking points to raise

Your direct experience building co-culture cell-killing assays. This is exactly the assay class behind ADC and bispecific potency.
Your Incucyte live-cell experience. Kinetic killing read-outs are highly relevant.
Your interest in making assays robust and transferable, not just getting one result.

Three things to look up before the interview

Aldbrook's website pipeline page. Note which ADC or bispecific programmes are public.
The difference between potency assays for ADCs and bispecifics, so you can speak to both.
What "assay transfer to QC" involves in a regulated setting (qualification, SOPs).

2. Predicted interview questions (with what they are really testing)

Competency and behavioural

Tell us about a cell-based assay you developed from scratch. (Can you own assay development end to end?)
Describe a time an assay gave inconsistent results. What did you do? (Robustness and troubleshooting mindset.)
How do you prioritise when you have several experiments competing for time? (Industry works to timelines and parallel projects.)
Tell us about a time you had to explain complex data to a non-specialist. (Cross-functional communication.)
Describe working as part of a team to hit a shared goal. (You will work across Discovery, Analytical, Process.)

Technical

Walk us through how you would set up a target-dependent cytotoxicity assay. (Core of the role.)
How do you design and validate a flow-cytometry panel? (Named requirement.)
How do you determine and interpret an EC50 or IC50, and what makes a curve unreliable? (Dose-response is the daily bread of this team.)
How would you move an assay from 96-well to 384-well format? What changes? (Throughput.)
What controls do you include in a cell-killing assay and why? (Rigour.)
How would you make an assay robust enough to transfer to QC? (The real ask.)

Motivation

Why are you moving from academia to industry? (Maturity of the decision.)
Why Aldbrook, and why oncology biologics specifically? (Genuine interest.)

Curveball

Tell us about a time you were wrong about a result. (Composure and honesty.)
What would you do in your first 90 days here? (Industry-readiness.)

3. Model STAR answers (built from Dr Reyes's real CV)

Q1. An assay you developed from scratch

S In my postdoc, we needed to measure antibody-mediated killing of HER2+ breast cancer cells but had no established read-out in the lab.

T I was responsible for building a co-culture cytotoxicity assay that could reliably quantify cell killing.

A I established the co-culture conditions, set effector-to-target ratios, built a flow-cytometry panel to distinguish live target cells, added the right controls, and cross-checked killing kinetics with Incucyte live-cell imaging.

R The assay became the lab's standard read-out for antibody-mediated killing and was reproducible enough that I trained two PhD students to run it. (Industry framing: reproducible, transferable, became a standard method.)

Q6. Setting up a target-dependent cytotoxicity assay

Draw directly on the co-culture HER2+ work: choice of target cells by antigen expression, effector-to-target ratio, time course on Incucyte, a flow read-out for live and dead target cells, and controls (no-effector, isotype or non-binding, max-kill). Emphasise reproducibility.

Q7. Designing and validating a flow panel

Use your PhD cell-death panel and your postdoc work: marker selection, fluorophore choice to minimise spectral overlap, compensation, FMO controls, and gating strategy. Stress that you have designed panels, not just run them, and that you trained others on the method.

Q8. EC50 and IC50 interpretation

You determined IC50 values for a panel of inhibitors in your PhD. Talk through fitting a dose-response curve in GraphPad Prism, what a good curve looks like (clear top and bottom plateaus, tight replicates, sensible Hill slope), and what makes one unreliable (no plateau, high replicate variability, too few points).

Q9. Moving from 96-well to 384-well

Even if you have mainly worked in 96-well, speak to the principles: smaller volumes increase edge effects and evaporation, mixing and pipetting precision matter more, you would re-optimise cell number and reagent concentrations, and you would verify Z-factor before trusting the format. (Honest bridge: "I have worked primarily in 96-well, and here is how I would approach the move.")

Q11. Making an assay transfer-ready

This is where you win the role. Talk about documentation, defining acceptance criteria and controls, characterising variability, writing a clear protocol someone else can follow, and qualifying the assay before handover. Tie it to having trained others to run your assays successfully, which is proof your methods survive leaving your own hands.

Q12. Why industry

"In academia I found the parts I enjoyed most were building robust assays and seeing them adopted by others. Industry is where that work has the most impact: assays that directly support getting a medicine to patients. I want to build methods that matter at that scale, in a team, to a shared timeline." (Motivated, not fleeing.)

Q14. A time you were wrong

Pick a real instance (for example an early co-culture result later traced to a control issue). Show you caught it, corrected it, and built a control in to prevent recurrence. Honesty plus rigour.

For any question where your CV does not give a strong example, prepare a real story in advance; do not invent one. A genuine example from your postdoc juggling the CRISPR screen alongside the cytotoxicity work will land well.

4. Academia to industry translation

Academic framing	Industry framing
"I developed a novel co-culture assay for my paper."	"I built a reproducible cell-killing assay that became the team's standard read-out."
"I optimised conditions for my experiments."	"I made the assay robust and trained others to run it reliably."
"I ran a CRISPR screen for my project."	"I designed and executed a screen to answer a defined question on a timeline."
"I analysed my data in GraphPad."	"I generate and interpret dose-response data and judge curve quality."
"I worked independently on my thesis."	"I owned a workstream end to end and handed methods over to others."

"Why I am moving to industry" (three sentences you can say): "The work I valued most in academia was building assays robust enough that other people could rely on them. In industry that robustness directly supports getting a therapy to patients, which is the impact I want. I am ready to do that work in a team, to shared timelines and quality standards."

5. Smart questions to ask the panel

About the role and team

"What does the assay-development team most need this hire to deliver in the first year?" (Shows you think in outcomes.)
"How does the team balance developing new assays against supporting existing programmes?" (Industry-real.)

About the science and pipeline

"Are the potency assays here mostly for ADCs, bispecifics, or both, and how do the approaches differ?" (Demonstrates genuine modality understanding.)
"How early does Assay Development get involved in a new programme?" (Cross-functional awareness.)

About growth and development

"What does success look like for someone in this role after 12 months?" (Maturity.)
"How does the team handle assay transfer to QC, and is that something I would be involved in?" (Signals you understand the regulated handover, which most academics miss.)
"What opportunities are there to grow technically or take on more responsibility?"
"How would you describe the team's culture on a normal week?" (Human, sensible close.)

6. Salary-negotiation script

Realistic UK range (general guide, not a guarantee). For an entry-level industry Scientist with a PhD at a Cambridge biotech, a typical base is roughly £38,000 to £48,000, with most first offers landing in the £40k to £44k band depending on the company and your interview strength. Treat this as a guide to calibrate expectations, not a promise.

When asked "what are your salary expectations?"

"Based on my research, I understand a Scientist role at this level in the Cambridge area typically falls in the low-to-mid forties. I am flexible and most interested in the right fit, but I would be looking for something in that range."

Responding to a first offer (anchor without antagonism):

"Thank you, I am really pleased and very keen to join. Would there be flexibility to move the base a little closer to the top of the quoted range? Given my direct experience with cell-killing assays and flow cytometry, I would hope to be near the upper end."

Non-salary levers if base will not move: a sign-on bonus, an earlier first salary review (for example at 6 months), the job title, holiday, or a training and development budget.

Graceful acceptance:

"That works for me. I am delighted to accept and looking forward to getting started."

Prepared by OfferReady. Built using general, public industry knowledge only. Good luck.