A Thursday in April, three dilution errors, a quality audit ten days out, and eight lab phones. How PhytoNote turned a DPPH session into four clean hours.
It was a Thursday in April, 1:45 PM. The level 2 bench room of the organic chemistry department at Mohammed V University still smelled like lunch-break coffee and the HPLC-grade methanol one student team had spilled walking in. I had fifteen Greiner 96-well plates to run with my M2 Phytochemistry students, on a classic DPPH assay applied to hydroalcoholic extracts of Thymus satureioides they had prepared the day before. Thirty students in pairs, one shared UV-1900 Shimadzu spectrophotometer, and the day's brief: deliver the IC50 of each extract before 5 PM.
When things start unraveling
After an hour, I had already spotted three problems. Pair 4 handed me their notebook and said "Madame, I have a doubt about the stock solution". They had prepared a 1 mg/mL solution instead of 100 µg/mL, and recorded the final concentration without correcting their dilution factor. Six wells lost. Pair 7 had forgotten to write down the weighed mass of their quercetin standard. The weighing existed somewhere in their short-term memory, but not on paper. And the room manager, Mme Lahcen, walked in with her logbook in hand: the DPPH• Sigma lot number was missing from every report submitted the previous week, and the department quality audit was ten days out.
I looked at the clock. 2:50 PM. Fifteen microplates left to read, students starting to flag, and a paper-based traceability system falling apart as the day went on. I had lived this scenario during my own PhD, except back then I was the only one paying the price. Now thirty people were waiting on a protocol that needed to hold.
Pulling out the phones
The lab has eight shared Android phones, bought last year on the training budget, which spend most of their time asleep in a locked drawer. I installed PhytoNote on all eight, in multi-user mode. I created one profile per student pair, loaded the DPPH-Thymus protocol I had written in YAML a few weeks earlier for my own runs, and told the students to leave their paper notebooks on the bench. They would keep writing in them, but double entry would go through the app.
First shock: the validation engine started shouting almost immediately. Pair 4 entered their stock dilution and the app refused. Concentration outside calibration range. A full-screen red alert with the message "check dilution factor". They reread their math, saw the inversion between stock and working solution, and corrected on the spot. Three minutes instead of half an hour of post-session debugging.
The second thing that struck me: mandatory entry of the DPPH• Sigma lot number when scanning the vial barcode. Mme Lahcen walked past me at 3:20 PM, glanced at a screen, and said "that flows straight into the report, does it?". I confirmed. She stayed on her feet for five minutes watching pair 12 weigh their standard.
Fifteen plates, 96 wells, 4:28 PM
From 3:30 PM onwards, things moved fast. Each pair took their turn at the Shimadzu, read their absorbances at 517 nm, and entered the values into PhytoNote as they walked out. IC50 calculation happened locally on the phone — four-parameter non-linear regression, 95% confidence intervals, all in under a second. Pair 9 got a curve with an R² of 0.87 and the app flagged it orange: "weak fit, consider repeat". They redid two wells, recomputed, R² climbed to 0.98. Validated.
At 4:28 PM, the fifteen plates were in. I launched the multi-sheet Excel export from my own phone, with one tab per pair, a summary IC50 tab, a metadata tab (lots, weighed masses, room temperatures, operator, timestamp). 2.3 MB. Sent by email to Mme Lahcen, to my two co-supervisors, and dropped on the department NAS.
Pair 2 got the lowest IC50, 38 µM in quercetin equivalent. Pair 11, the highest, 142 µM, probably because their extract had sat at room temperature through the lunch break. We discussed it all together during the last twenty minutes of the session, curves projected from my phone via the app. No student had to rewrite their numbers on the blackboard.
What Mme Lahcen asked on her way out
While the students put away their pipettes and I cleaned the bench, Mme Lahcen came back with her logbook. She asked a simple question: "can we roll this out to the L3 sessions?". The L3 cohort cycles 80 students through the same experiments twice a week, and responsibility falls on three technicians who spend their Friday afternoons piecing reports back together from illegible photocopies of paper notebooks.
I said yes, on one condition: we take two weeks to translate the L3 protocol into YAML, validate the calibration ranges, and train the technicians beforehand. She agreed. We start the week of May 6th.
Driving home to Rabat that evening, I thought back to my own master's sessions in 2014, when I would spend Friday nights copying numbers into an A4 grid notebook, hoping I wasn't skipping a line. The paper notebook still matters — for the signature, for the legal trace, for what it represents as a rite of passage for a researcher. But fifteen 96-well plates in four hours, with thirty students, is not something you can do by hand anymore without accepting a 10 or 15% error rate.
The barcode on the DPPH• Sigma vial, the protocol YAML, the timestamped Excel export: all of that now exists as a layer above the notebook, not in its place. Which is exactly what I had been hoping for when I started writing PhytoNote two years ago, after a lab session that looked oddly like this one.
If you want to see how the app works in multi-user mode for supervised lab sessions, I go into more detail on the PhytoNote product page. For the full method and validation protocol, the paper is here. The same data-entry bottleneck caught me a few weeks later at EMINES, with a single shared Nikon for twelve students — I told that story in the workshop recap.