How To Optimize a Preclinical Vaccine Trial
Ok, this is the moment you have been waiting for – since the beginning of your scientific career – you finally get to vaccinate something. The hundreds, if not thousands of hours spent in the lab, the late nights and weekends spent developing the vaccine, making sure it is specific for your antigen, purifying it, looking at primers, proteins, DNA, RNA, adjuvants, is finally all going to pay off in this preclinical trial. You will now demonstrate to the scientific world, or at least your principle investigator (PI), that your vaccine is safe and efficacious at preventing infection or targeting the cancer antigen. This vaccine will change the direction of your research, it will go into non-human primates next, and before you know it, you will be submitting an institutional review board (IRB) application to get it into humans and Ta-Da … you solved the next big thing. Or it will completely fail, the vaccinated group will die and the unvaccinated will live, and you have to start from the beginning – day one. Either way, you’re good. Believe me – either way, you will obtain some very useful information, and this is the truth. Success or failure will provide insight on the hundreds of aspects of the vaccine, animal model, disease, immunology and vaccine strategy, you will save the next group unnecessary work and hundreds of hours of trial and error based on your study. So, no matter what happens, you are good, you are contributing to the knowledge base of your specific disease. Congratulations!
I cannot emphasize this point enough. Any decent size vaccine trial, even an indecent size, can become unwieldly fast, in other words a “master calendar” is not only essential, it is vital to the success of the study and the sanity of the researchers. Keep the calendar simple, choose one that works for all lab members involved, keep a master calendar (hard copy) in the lab, keep a version in the lab notebook and make sure all members have a digital or paper copy. No one should ever say: “I didn’t know I was priming, vaccinating, boosting, challenging, collecting samples today.” It is a good idea to have only one person in charge of the calendar, and fair or unfair, this person is also the one that will have to remind others to look at the calendar because something is to be done next week. If a time point is missed, a boost not completed, or samples forgotten to get sampled, you cannot repeat that time point; it is gone, never to be seen again. The immune response is past that point and it cannot go back. A missed date will result in gaps in your data, your graphs will look funny, your stats may be off, and you will have to explain it in your results and discussion. Have a backup person for every time point, who will come in and take care of it if someone is sick or on leave. To all others, you are all professionals, you are all busy, but everyone has made a commitment to the success of this study. Keep your version of the calendar up to date, set your own reminders and maybe you can be the one that no one ever has to remind!
Study design: Timing and sequence is extremely important, but often arbitrary
I am often asked, how do I determine when to prime, vaccinate, boost or challenge animals in the study, in the case of an infectious disease study, or when to implant tumors in the case of a cancer vaccine study. My answer: “it is totally arbitrary”. You are developing your specific vaccine strategy and doing this study because no one has figured it out, you are the one that is figuring out the optimal vaccine strategy. So often there is no “template” to follow, you are it. Don’t panic, the good news is that you can use the many failures of other labs as your inspiration. Chances are most vaccine trials in your field have tried something similar, so your starting point is the literature. By this time in your research, you should be more than familiar with the previous studies, so make the necessary changes you think will bring you success – from spacing the vaccine timelines, boosting, priming, or challenging sooner, or implanting later. Keep in mind the changes you make must be realistic for animals (veterinary vaccine) or humans. The goal of any vaccine trial is for it to someday be administered to animals or humans. Is it realistic for a vet to boost any animal twice a month versus one prime and one boost 8 weeks apart? For humans, a prime and maybe a boost in six months is more realistic versus a prime and 2 boosts close together. In the case of cancer vaccines, since cancer progression is often aggressively fast, prime and boosts may need to be very close together, to give the cancer a one-two punch. It is important to keep in mind the end goal of your study, keep in mind the disease or condition you are fighting and the best way to beat it.
Determine experimental and control groups at the outset
Even if the vaccine does not protect against infection or decrease tumor size, other data can be acquired from the trial – is the vaccine immunogenic, is there a strong or weak response, what is the breadth of the response. Is there some protection – it may not prevent 100% infection, but compared to the control is there a difference? Same with a cancer vaccine, if the tumor has not completely regressed, is there a significant size difference compared to unvaccinated animals? These and other parameters can be determined and analyzed if there are appropriate experimental and control groups. As with any animal study, it is important to use the minimum number possible to obtain statistically significant data and to follow all protocols and regulations, Federal, State, Local and University. I have used as little as N=6 for a mammal study (cats); and as many as N=15 (mice). If there is an issue regarding animal numbers, then you must determine the importance of control groups and experimental groups.
If you must omit a specific control group, it is imperative to go through the various scenarios of how you will interpret the results without that specific control group. It would be wise for the lab to gather around the conference table with pizza and soft drinks and go through each scenario with and without certain control groups. At an absolute pinch, historical data, or a control group can be used – provided it has been used so many times that it is a “known and accepted” group, this is a rare case and it would be better if your lab has the historical data. If an important control group is left out of the trial, results from experimental groups may not show relevance or differences in responses to the vaccine. How can a vaccinated group’s efficacy be compared if the control group with adjuvant only, or vector only or unchallenged are missing, this can void any results you “see” in the experimental group. Use established animal models if this is the first attempt at a preclinical vaccine trial.
Reagents. This may seem obvious, but make sure you have enough reagents, especially vaccine
Vaccine must be from the same lot if you are acquiring it from a company or another lab. If you are making your own vaccine, try to make enough for the whole study, I know this is not always possible due to “freshness factors”, but you can make sure you are using the same vaccine antigen stock – make enough to freeze back and use to make additional vaccine if needed. Try to get enough assay reagents, especially if using kits of the same lot, if not, it must be noted each time a different lot of any reagent is used. Lastly, try to have extras, tubes get dropped, animals move (meaning you miss the mark with the needle), freezers breakdown. Do everything you can to ensure you have backups, this will eliminate stress and panic when something goes amiss with reagents.
Documentation is extremely important
Write down everything even if it seems insignificant to the study, you won’t know if it is important until you start to analyze the data. Don’t just write down the data and observations, tell a story, a narration, that way when you or someone else goes back to your notebook they can follow the story and perhaps know why you made certain choices and decisions, why you chose certain assays or reagents, etc. Thus, the wheel does not have to be reinvented and past mistakes will not be repeated.
NEVER change the protocol of a study under any circumstances
The protocol you started with is the best one your lab devised, so you must not make any changes once the trial has started. Even if you observe your animals dying, getting sicker and the study is not going how you thought, even if you think that this is a great big failure, DO NOT make any changes. Even if a trial fails, which it may, any and I mean any information you get from this study is extremely important for the next study or for immunogenicity, efficacy, toxicity, dosage responses, biomarkers, endpoints primary and secondary, the list goes on. Of course, sometimes time points are missed, too many doses are given, or something is forgotten, we are human, it happens. In these cases, document everything, what happened, to what group, did you try to “fix” it, how and why, did you decide to let it be? Accidents happen, record everything, but do not change the study purposefully – to suit your preconceived outcomes, the goals of the grant or grantor. Don’t be “that” lab, the lab that must make “changes” due to “accidents”, it just makes you look sloppy and unprofessional.
Very funny, there is none. Be willing to come in on weekends and evenings, time points, assays, sample collections do not always occur between 9:00–5:00 Monday to Friday.