INTRODUCTION
Over the last 20 years, high throughput screening (HTS) has been the dominating drug discovery approach, with multimillion compound libraries being build and screened against well-established targets \cite{Settleman_2016}. Recently, pharmaceutical companies have been investigating novel ways to add compound annotation beyond the chemical structure and the desired on-target effect, with the aim to reduce attrition and increase hit rates for more complex targets \cite{Smietana_2016}. In this context, Lamb introduced the Connectivity Map (i.e. CMap), in which 1309 compounds were transcriptionally profiled in four human cell lines, using the Human Affymetrix U133 platform \cite{Lamb_2006} \cite{Lamb_2007}. Compound induced differential expressed genes could subsequently be translated into gene signatures, which could potentially be used to discover new connections among compounds, pathways, diseases and/or phenotypic states in general \cite{Lamb_2006}. Since the introduction of CMap, technological advances have been made which helped to revolutionize high throughput transcriptional profiling in drug discovery and development. Peck \cite{Peck_2006} developed for instance, a transcriptional profiling method, involving a ligation-mediated amplification in which the amplification products of 100 transcripts were captured on fluorescently addressed microsphers, using a flow cytometric detection technique. This technology, was further developed at the Broad institute to accommodate the direct measurement of 978 carefully selected human gene transcripts. Known as L1000 and commercialized by Genometry Inc (Cambridge, MA, US), this automated assay can now be used to screen and measure the transcriptionally induced effect(s) of thousands of compounds per day at a cost far below conventional transcriptomic techniques like microarrays \cite{Subramanian_2017}. As such, L1000 enabled the generation of more than a million transcriptional profiles, for over 19811 small molecule drugs, tool compounds and screening library compounds across 3 to 77 cell lines, in the NIH-funded and public available LINCS program \cite{Subramanian_2017}. Both CMap and L1000 have since then been succesfully applied to find new therapeutic targets \cite{Lamb_2006},\cite{Liu_2015}, \cite{Won_2015} \cite{Senkowski_2016}, repurpose or reposition existing drugs \cite{Iorio_2010}, \cite{Kunkel_2011}, \cite{Ramsey_2013} and/or flagg side effects \cite{Wang_2015}.
L1000 introduction in Janssen and L1000 effort of 230K cpds of primary screening deck
With this effort we want to demonstrate the usefulness of L1000 in complex settings
Example HBV (content on disease, cccDNA, literature on APOBEC3B, disease gene signature)
Link HBV-L1000 (disease expressed in the same language as the 230K cpds)
HBV