Literature-related discovery (LRD): Lessons learned, and future research directions

Ronald N. Kostoff a, Joel A. Block b, Jeffrey L. Solka c, Michael B. Briggs d, Robert L. Rushenberg

e, Jesse A. Stump f, Dustin Johnson g, Terence J. Lyons h, Jeffrey R. Wyatt i

Technological Forecasting & Social Change 75 (2008) 276–299

a Office of Naval Research, 875 N. Randolph St., Arlington, VA 22217, USAb Section of Rheumatology, Rush Medical College, Rush University Medical Center, 1725 W. Harrison St., Suite 1017, Chicago, IL 60612, USAc Naval Surface Weapons Center Dahlgren Division, Dahlgren, VA 22448-5100, USA, d Arlington, VA 22204, USAe DDL-OMNI Engineering, LLC, 8260 Greensboro Drive, McLean, VA 22102, USA, f Catonsville, MD 21228, USA, g Arlington, VA 22201, USAh Air Force Office of Scientific Research, Arlington, VA 22203, USAi DDL-OMNI Engineering, LLC, 8260 Greensboro Drive, McLean, VA 22102, USA

Kathleen Padova, November 18, 2014

PublicationTechnological Forecasting & Social Change v75 i2 (2008) - Literature-Related Discovery - Edited by Ronald N. Kostoff• Literature-Related Discovery (LRD): Introduction and background, (165 – 185) Ronald N. Kostoff• Literature-related discovery (LRD): Methodology (186 – 202) Ronald N. Kostoff, Michael B. Briggs,

Jeffrey L. Solka, Robert L. Rushenberg• Literature-related discovery (LRD): Potential treatments for Raynaud's Phenomenon (203 – 214),

Ronald N. Kostoff, Joel A. Block, Jesse A. Stump, Dustin Johnson• Literature-related discovery (LRD): Potential treatments for cataracts (215 – 225) Ronald N.

Kostoff• Literature-Related Discovery (LRD): Potential treatments for Parkinson's Disease (226 – 238),

Ronald N. Kostoff, Michael B. Briggs• Literature-related discovery (LRD): Potential treatments for Multiple Sclerosis (239 – 255) Ronald

N. Kostoff, Michael B. Briggs, Terence J. Lyons• Literature-related discovery (LRD): Water purification (256-275) Ronald N. Kostoff, Jeffrey L.

Solka, Robert L. Rushenberg, Jeffrey A. Wyatt• Literature-related discovery (LRD): Lessons learned, and future research directions (276 - 299)

Ronald N. Kostoff, Joel A. Block, Jeffrey L. Solka, Michael B. Briggs, Robert L. Rushenberg, Jesse A. Stump, Dustin Johnson, Terence J. Lyons, Jeffrey R. Wyatt

Post-publication

• Literature-related discovery, Annual Review of Information Science and Technology Volume 43, Issue 1, pages 1–71, (2009)

• Literature-related discovery: Potential treatments and preventatives for SARS, Technological Forecasting and Social Change, (2011)

• Literature-related discovery and innovation — update, Technological Forecasting & Social Change 79 (2012)

• Literature-related discovery techniques applied to ocular disease: a vitreous restoration example, Current opinion in ophthalmology, (2013)

• Literature-related discovery: Common factors for Parkinson's Disease and Crohn's Disease, Scientometrics (2014)

• Literature-related discovery and innovation: Chronic kidney disease, Technological Forecasting and Social Change in progress (Nov 2014)

Literature-Related Discovery

• Components– Literature-based Discovery– Literature-assisted Discovery

• Types– Open Discovery Systems– Closed Discovery Systems

LRD Literature Properties

• All the literatures should be complementary • All the literatures should be disjoint• All these literatures should be as

comprehensive as possible• All these literatures with unique information

must be linked to form a whole that is greater than the sum of its parts.

Summary of Generic Approach to ODS LRD

1. Retrieve core literature of target problem2. Characterize core literature3. Expand core literature4. Generate potential discovery

Step 1: Retrieving Core Literature

• Very, very, very, important step• Complete and comprehensive • Query and Bibliometrics

Steps 2 & 3: Characterize core literature and expand

• Extract main topics from Step 1 using clustering

• Use these new terms/phrases to expand the literature set

Step 4: Discovery

• Identification of potential discovery candidates

• Drawing the linkages between the potential discovery candidates and the core literature

• Vetting– Manually reviewing candidates, with experts

Approach for non-medical studies

• Doesn’t have the benefit of taxonomy• Cluster Semantic Filtering – Manually examination of clusters, select

semantically relevant• Latent Semantic Indexing– Tagged articles with core query terms– Clustered into thematic group and used terms to

expand– Ranked terms using similarity score

Study Applications

• Medical– Reynaud’s Phenomenon– Cataracts– Parkinson’s Disease– Multiple Sclerosis

• Non-medical– Water Purification

Multiple sclerosis

• Neurological disease• Auto-immune disease• Variety of symptoms• No cure• No known cause

Multiple Sclerosis Study Goals

1. Prevent the occurrence, or reduce the progression rate, or stop the progression, or maybe even reverse the progression, of MS

2. Demonstrate they could solve LRD problem with no prior knowledge of results or prior work

3. Generate large amounts of potential discoveries in less time

Multiple Sclerosis Study Approach

• Retrieve Core MS Literature– Query “Multiple Sclerosis”

• Directly related literature– demyelination and remyelination; indirect

autoimmune contributors to inflammation/blood–brain barrier; direct autoimmune contributors to inflammation; myelin basic protein, and viruses, diagnostic, treatment, symptoms, etc

• Auto-correlation maps and factor matrix analysis

Multiple Sclerosis Factor Groups

• Factor 1: Myelin sheath proteins and maintenance cells (myelin basic protein; myelin oligodendrocyte glycoprotein*; proteolipid protein*; experimental autoimmune encephalomyelitis; oligodendrocyte*; encephalitogenic; epitope*; immunization; immunodominant)

• Factor 2: Indirect contribution of lymphocytes to inflammation by secretion of cytokines, chemokines, and lymphokines (cytokine*; tumor necrosis factor-alpha; peripheral blood mononuclear cells; interferon-gamma; proinflammatory; interleukin*)

• Factor 3: Viral contributions to inflammation (murine encephalomyelitis virus; virus; viral; demyelinating)

• Factor 4: Autoimmunity (cerebrospinal fluid; oligoclonal IgG bands; isoelectric focusing; glial fibrillary acidic protein; Intrathecal IgG; IgG index; immunofixation; electrophoresis)

• Factor 5: Demyelination and remyelination (oligodendrocyte*; demyelinate*; glial fibrillary acidic protein; astrocyte*; axon*; myelin oligodendrocyte glycoprotein*; remyelinat*)

• Factor 6: Blood–brain barrier (vascular cell adhesion molecule-1; intercellular adhesion; ICAM-1; endothelial; endothelial cell*; cell adhesion molecule; endothelium).

Multiple Sclerosis Query Development

((demyelinate* OR remyelinat* OR “myelin sheath pathology” OR (“myelin sheath” AND (damage OR degenerate*)) OR “axonal loss” OR “axonal destruction” OR (oligodendrocyte* AND (apoptosis OR death OR degenerate* OR damage OR dystrophy)) OR (oligodendroglia* AND (apoptosis OR destruct* OR loss))) OR (“blood–brain barrier”AND (disruption OR “ell adhesion”OR “ctivated lymphocyte*”OR “dhesion molecule*”OR (lymphocyte* AND trafficking) OR breakdown OR transmigration OR dissolution)))) NOT “multiple sclerosis”

Multiple Sclerosis Results

• Non-drug concepts within MS Core literature– Vitamin D– Green Tea– Qeuecetin– Caloric Restriction– Synthetic metal ion chelators– Specific herbal ingredients

• Non-drug potential discovery concepts in the directly related literature– Kalpaamruthaa – rheumatoid arthritis– Salvia miltiorrhiza Bunge – atherosclerosis– Inchinko TJ-135 - hepatitis

Multiple Sclerosis LRD Summary

• Synergy of lifestyle/dietary practices• Non-discovery –

– Vitamin D, dietary chelators, caloric restriction, complement-inhibitory herbs, Nigella sativa oil, green tea, and quercetin

• Potential Discovery – – Shogaol, Ethanol, Iron, Petaslignolide A, Mangifera indica L,

Tiliroside, Gnaphaliin, Cissus quadrangularis extract, Kalpaamruthaa, Salvia miltiorrhiza Bunge, Inchinko TJ-135, Silymarin, Edaravone, Sopoongsan, and Artemesia iwayomogi

• Disconnection between mainstream and major medical websites/journal review papers (core MS literature) and related literature

Limitations of Approach to MS Study

• Not all possible semantic categories identified

• Relatively few terms selected from the queries

• Not all retrieved records were examined

• Skipped citations linking

Lessons Learned*

• Selecting the most important concepts from extremely large volumes of potential discovery retrieval

• Topical specialist(s) working closely with information technologist(s)

• Functional query with clustering and semantic filtering

• Bibliographic coupling • Literature deficiencies major obstacle to progress– Skewing of technical literature – treatment over cause– Under-estimation of prior art

Literature-related discovery and innovation — update

• Technological Forecasting & Social Change 79 (2012) 789–800

• Ronald N. Kostoff – Georgia Institute of Technology, School of Public Policy

Literature-related discovery and innovation — update

• Literature-Related Discovery and Innovation (LRDI)

• Compared results of previous LRDI study on MS to a documented reversal of MS– The Wahls Protocol: How I Beat Progressive MS

Using Paleo Principles and Functional Medicine By Terry Wahls M.D., Eve Adamson

Literature-related discovery and innovation — update

• Past LRDI study identified potential causes and potential non-drug treatments

• Dr. Wahls’ diet could have been obtained from 2007 literature set

• Literature never mentioned nutrition components in conjunction with MS

• One of Dr Wahl’s treatments (NMES) was not strong in literature

• LRDI itself is not provable, Dr. Wahls was personally affected to follow treatment – ‘skin-in-the-game’

Discussion

• The LRD techniques presented by Kostoff were still manually intensive, the techniques presented by Spangler, et al. were more systematic - how much human element can be offloaded to computers?

• Kostoff’s LRDI techniques strongly depends on controlled language and he discussed techniques for studying topics without a controlled vocabulary/taxonomy – are there other approaches?