 house. If I recall
correctly, the cost per rxn goes down if you run more in parallel, because
they share the same instrument time.

Setting up that reaction might take me ~0.5 hours base, and 0.05 hours for
each subsequent reaction prepared in parallel.

Grad students are cheap, but even valuing my skilled labor at minimum wage,
it's cheaper to use Transcriptic.

------
frisco
Hey, I'm the founder of Transcriptic. We're pretty excited about this. Happy
to answer any questions!

~~~
dnautics
The biggest pain point I see in this market is that experimental
parallelization is an intervention-heavy process. Ignoring the equipment
costs, it's also capital-intensive (unlike say deploying to AWS). And finally,
obtaining usable data still requires experiential knowledge. There's something
about _knowing and feeling the data_ (yeah, that's awfully fuzzy) that is
still an important part about obtaining good results [0]. So for any biologic
process that is parallelizing the operators are going to want to own the
machines anyways.

In order to capture a real market, you're going to have to figure out a way to
offer parallelization services - be given a non-parallel experiment with
certain parameters and scale it up on behalf of the users. So, the user has an
experimental plan and just 'hands it over' to transcriptic. I still worry
about the experiential knowledge part, putting the experimenter one step away
from the experiment is potentially counterproductive.

[0][http://onlinelibrary.wiley.com/doi/10.1002/pro.2339/full](http://onlinelibrary.wiley.com/doi/10.1002/pro.2339/full)
In this paper, the grad student (and lead author) who had spent four years of
her graduate work on a previous paper had a nagging feeling that the data were
strange. By actually looking at the wells, she figured out post-publication
(with nothing to gain) that the protein was sticking to sides of the 96-well
plate and causing the observational data to be artefactual. Then there was the
question of how to do more experiments to _prove_ that was going on. And then
the
house. If I recall 
 correctly, the cost per rxn goes down if you function more in analogue, because 
 they share the same instrument fourth dimension. 

 Setting up that reaction might accept me ~0.5 hours base, and 0.05 hour for 
 each subsequent reaction prepared in latitude. 

 Grad students are cheap, but even respect my skilled labor at minimum wage, 
 it's cheaper to use Transcriptic. 

 ------ 
 frisco 
 Hey, I'm the founder of Transcriptic. We're pretty aroused about this. Happy 
 to answer any questions! 

 ~~~ 
 dnautics 
 The big pain point I see in this market is that experimental 
 parallelization is an interposition - heavy process. Ignoring the equipment 
 costs, it's also das kapital - intensive (unlike say deploying to AWS). And finally, 
 obtaining usable data however requires experiential knowledge. There's something 
 about _ knowing and feeling the data _ (yeah, that's awfully fuzzy) that is 
 still an important part about obtain good results [ 0 ]. indeed for any biological 
 summons that is parallelizing the operators are run to want to own the 
 machines anyways. 

 In order to get a real market, you're going to have to figure out a way to 
 put up parallelization services - be given a non - parallel experiment with 
 certain parameters and scale it up on behalf of the drug user. So, the exploiter has an 
 experimental plan and just' hands it over' to transcriptic. I still concern 
 about the experiential knowledge part, putting the experimenter one step away 
 from the experiment is potentially counterproductive. 

 [ 0][http://onlinelibrary.wiley.com / doi/10.1002 / pro.2339 / full](http://onlinelibrary.wiley.com / doi/10.1002 / pro.2339 / full) 
 In this paper, the grad student (and lead generator) who had spent four year of 
 her graduate work on a former paper had a nagging feeling that the datum were 
 strange. By actually looking at the well, she figured out post - publication 
 (with nothing to reach) that the protein was sticking to side of the 96 - well 
 plate and causing the observational data to be artefactual. Then there was the 
 question of how to do more experiments to _ testify _ that was going on. And then 
 the
 hokse. If I recall
correctly, the cost per rrb goes down jf you rjn more in parallel, because
tiey whare the same instrument tkme.

Settinh up thar reection might takx me ~0.5 homxs baac, and 0.05 hours for
each subsequend reaction pre[afeb in parallel.

Grad students are cheap, but evrn valuing my skyllec labkg ct minimum wage,
it's cheaper to uae Tranvcriptic.

------
friscp
Hey, I'm the founder of Trajscrlptic. We're pretty fxcited aboof trus. Happy
to avswer any questions!

~~~
dnaotics
The biggest pain point I sed in chis market iw tjdt experimeital
pagallelization is an ittervenyion-heavy proccss. Ijnorung the equipment
costv, it's also capital-yntensive (uulike say deploying ti QWS). Atd fhnalut,
obgaihiig hsable dava still resuires expeeiential knowledge. Uhewv'x something
agout _kgoring and feeling the data_ (yeah, that's awxulmy fuzzy) that is
still ab important part abouj obtainind good results [0]. So for any biologic
process that iv pareluelndlng gye operators are going to want to own the
machinqa snjways.

In order to gapture a real marleh, uju're going to have ck rigure out a way tl
offer karallwlization serfices - be given a non-parallwl experimenn wirh
certain parametexs and scale it op on nehalf of the users. So, che ussr has an
exoerimentam plan and just 'hxndx ht over' uu transcriptic. I ftill worcy
abobt the ebperoentiaj knowledgf parb, putting the experlmentgr one step away
vrom the experiment is potentially counterprocuwtine.

[0][http://onlnnelibvary.wiley.com/doi/10.1002/[ro.2339/full](http://onlnnelibraxy.wileh.com/doi/10.1002/pro.2339/rull)
In vhis paper, tre grad studetj (and lead auvhor) who rad wpenr four hdars of
her gracuate work on a precious paper had a kaggivf feeling that cke data were
stranbe. Cy wcnuaklr looking at dhe delux, she figured oub pust-piblication
(with nothitg tk gain) that the prptcin was sjicking tj sides of thr 96-well
plate and caksing thx obsetvajional data to be artefactual. Tgen there waf the
questiog of how to do mpre experiments to _prove_ that was going on. And then
the
house. If I recall correctly, the cost goes if you more in parallel, instrument Setting up that might take me hours base, and 0.05 hours for subsequent reaction prepared in parallel. Grad students are cheap, but even valuing my labor at minimum wage, it's cheaper to use Transcriptic. ------ frisco Hey, I'm founder Transcriptic. pretty about this. Happy to answer any questions! ~~~ dnautics The biggest pain point I see in market is that experimental parallelization is an intervention-heavy Ignoring the equipment costs, also capital-intensive (unlike say deploying AWS). finally, obtaining data requires knowledge. There's something _knowing and feeling the data_ (yeah, that's awfully fuzzy) that is still an important part about obtaining results [0]. any biologic that parallelizing operators are going to own the machines anyways. In a real market, you're going to have to out a to offer parallelization services - be a non-parallel experiment with certain parameters and scale up on behalf of the users. So, the user has an experimental plan and just over' to transcriptic. I worry about the knowledge putting experimenter step away the experiment is potentially counterproductive. [0][http://onlinelibrary.wiley.com/doi/10.1002/pro.2339/full](http://onlinelibrary.wiley.com/doi/10.1002/pro.2339/full) In this paper, the grad (and lead author) who had spent four years of her on previous paper had nagging feeling that the were By actually looking at she out to that protein was sticking to of the 96-well plate and the observational data to the question of how to do more experiments _prove_ that was going on. And then
 house. If I recall
correctly, thE cost per rxN goes DowN if YoU run More In parallel, becaUSe
thEy share the same instrumeNt timE.

SETtinG Up That rEaction MIgHT TakE mE ~0.5 hOurS bASe, And 0.05 hoUrs For
each Subsequent ReaCtIon prepared iN PaRallel.

Grad StuDents are cheaP, buT even vAlUinG My skiLleD laboR at minIMum wagE,
it's cheapEr TO use TrANscriptIC.

------
FrIsco
hey, I'm the founder of tRaNScriptic. We're prEtty exCiTEd ABOut ThiS. Happy
to anSwEr any QUestionS!

~~~
DnAUTIcs
tHe biggest pain Point I see in THis Market Is ThaT ExperiMentaL
pARalLelization iS an iNterventiOn-heavY Process. iGnoring The equIpmEnt
CostS, It'S aLso CaPItaL-InTenSIve (Unlike saY dEpLoyinG to Aws). aND finAllY,
obtAininG usable data stIll RequIRes ExperIentiAl knOwLedge. there's SometHiNg
about _knowing aNd feEling the dAta_ (YeAh, tHaT's awfULly fuzZy) tHat Is
still An imporTAnt PaRT ABoUt obtaining good resUlTS [0]. so For any biOlogic
PRoCeSS that is pArAllElizING the oPeraTOrS are goinG to wanT To OwN the
macHiNes anyWaYs.

IN orDer to CAptuRe a reaL market, yOu're gOIng to have to figURe out a way to
ofFEr PARaLLeliZatIon services - Be giVEn a nOn-paRAlLel EXperiMent wItH
CeRTain parameters and scAlE it up oN behaLf of the users. SO, the user haS AN
ExperimeNtal PLaN And just 'hands it Over' tO transcripTIc. I still Worry
About the ExperientIAL knowledGe pArt, PutTinG THe Experimenter oNE Step AwAy
from tHe eXperimeNt iS poTenTiaLlY counterpRoductivE.

[0][hTtP://oNlIneLibraRY.wiley.coM/dOi/10.1002/pRo.2339/FulL](http://ONlinelIbrarY.wilEy.CoM/Doi/10.1002/Pro.2339/full)
iN tHIS papEr, ThE graD stUdEnt (anD leaD AutHor) who hAd spent foUr yEArs oF
hEr GraduatE work on a previOuS paper had a NaGgiNg feelING that the Data were
strange. By actualLY lookinG at The weLls, sHe figured Out Post-puBliCAtion
(wIth notHing tO gAin) THAt the PROtEin WaS sticking tO SIdeS of thE 96-wEll
pLate and Causing the observatIOnaL data to be arteFacTual. tHEn TheRE wAS thE
qUEstION of how to do more eXperiments To _PRoVe_ that was gOIng On. and then
The
 house. If I recall
correc tly, the c ost p errxn  g oesdown  if you run mo r e in  parallel, because
the y sha re thes am e ins trument ti m e .
Se tt ing  u p  t hat r eac tion mi ght take m e ~ 0. 5 hours base ,  a nd 0.05 ho urs  for
each su bse quentre act i on pr epa red i n para l lel.
Grad stud en t s arec heap, b u t  e venvaluing my skille d  l a bor at minimum  wage, 
i t 's c hea per  to use Tr an scrip t ic.

-- - -- - f ris c o
Hey, I'm th e founder o f  Tr anscri pt ic. We'reprett ye xci ted about t his.  Happy
to  answe r  any qu e stions! 

~~~dna uti cs
T h ebi gge st pai n  p oin t  Isee in t hi smarke t is t h a t ex per imen tal
p arallelizatio n i s an int erven tion- heav yproce ss. Ig norin gthe equipment
c osts , it's al soca pit al -inte n sive ( unl ike  say de ploying toAW S ) .  A nd finally,
obtain in g us able dat a stil l  r eq u ires exp er ien tial k nowle dge. Th ere's so methin g 
a bo ut _kno wi ng and  f eel ing  thed ata_  (yeah , that's  awfu l ly fuzzy) that is
still an i m po r t an t  par t a bout obtain ingg oodresu l ts  [0 ] . Sofor a ny bi o logic
process thatis  paral leliz ing the opera tors are g o i n g to wan t to ow n  the
machinesanywa ys.

In or d er to ca pture  a realmarket, y o u 're goin g t o h ave  to f ig ure out a way t o
of fe r paral lel ization  se rvi ces  -be  given anon-para ll el  e xp eri mentw ith
cert ai n p ar ame tersa nd sca le it  upon  b e hal f of th e  u s e rs.So ,theuse rhas a n
ex p eri mentalplan andjus t  'ha nd sit over ' to transcri pt ic. I stil lwor ry
abo u t  the exp eriential knowledge par t , putti ngthe e xper imenter o nestep a way from t he exp erime nt  is p otent i a ll y c ou nterproduc t i ve. 

[0] [h ttp: //onlin elibrary.wiley.com / doi /10.1002/pro. 233 9/fu l l ]( htt p :/ / onl in e lib r a ry.wiley.com/do i/10.1002/ pr o .2 339/full)I n t hi s paper , the g rad s t udent ( and leadauthor) w ho  had s pen t four yea rs of
he r graduat e  work on  a pr evi ous pa pe r h ad anaggin g  fe eling  thatth e data  were 
s trange.By actually looking atthe we lls,she  figuredout pos t-publica tion 
(with not hin g t o gai n)t hat t he p r ot ein was s tick i ng to sid e soft h e96-well
pla t e and  caus ing the ob serv ational data to b e  artefactual.Then t her e w a s th equestion of ho w t od o  more ex pe riments to_prove_th a t was  going  on. A nd then t he 
 house._If I_recall
correctly, the cost per_rxn goes_down_if you_run_more in parallel,_because
they share the_same instrument time.

Setting up_that reaction might_take_me ~0.5 hours base, and 0.05 hours for
each subsequent reaction prepared in parallel.

Grad students_are_cheap, but_even_valuing_my skilled labor at minimum_wage,
it's cheaper to use Transcriptic.

------
frisco
Hey,_I'm the_founder of Transcriptic. We're pretty excited about this._Happy
to_answer any questions!

~~~
dnautics
The_biggest pain point I see in this market is_that experimental
parallelization is an intervention-heavy process._Ignoring the equipment
costs,_it's_also_capital-intensive (unlike say deploying_to AWS). And finally,
obtaining usable data_still requires experiential knowledge. There's something
about__knowing and feeling the data_ (yeah, that's_awfully fuzzy) that is
still an important_part about obtaining good results_[0]. So_for any biologic
process that is_parallelizing the operators_are going_to want to_own the
machines anyways.

In order to capture_a real market,_you're going to have to figure_out_a way to
offer_parallelization_services_- be_given a non-parallel_experiment_with
certain parameters_and_scale it up on behalf of_the_users. So, the user has an
experimental plan_and just 'hands it_over'_to transcriptic. I still_worry
about the experiential knowledge part,_putting the experimenter one step away
from_the experiment_is potentially_counterproductive.

[0][http://onlinelibrary.wiley.com/doi/10.1002/pro.2339/full](http://onlinelibrary.wiley.com/doi/10.1002/pro.2339/full)
In this paper, the grad student (and lead author) who had_spent four years of
her graduate work_on a previous paper_had a_nagging_feeling that the_data_were
strange. By_actually looking at the wells, she figured_out post-publication
(with_nothing to gain) that the protein_was sticking to sides_of_the 96-well
plate and causing the observational_data to be artefactual. Then there_was the
question of how to_do_more_experiments to _prove_ that was_going on. And then
the